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Add documentation sources for FANN extension

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Jakub Zelenka 2013-08-28 19:06:34 +00:00
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76
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<?xml version="1.0" encoding="utf-8"?>
<!DOCTYPE book PUBLIC "-//OASIS//DTD DocBook XML V5.0//EN"
"{PATH_TO_DOCBASE}/docbook/docbook-xml/docbook.dtd" [
<!-- $Revision$ -->
<!-- We use xhtml entities all over the place -->
<!ENTITY % xhtml-lat1 SYSTEM "{PATH_TO_DOCBASE}/entities/ISO/xhtml1-lat1.ent">
<!ENTITY % xhtml-symbol SYSTEM "{PATH_TO_DOCBASE}/entities/ISO/xhtml1-symbol.ent">
<!ENTITY % xhtml-special SYSTEM "{PATH_TO_DOCBASE}/entities/ISO/xhtml1-special.ent">
<!ENTITY % isopub SYSTEM "{PATH_TO_DOCBASE}/entities/ISO/isopub.ent">
%xhtml-lat1;
%xhtml-symbol;
%xhtml-special;
%isopub;
<!-- Fallback to English definitions and snippets (in case of missing translation) -->
<!ENTITY % language-defs.default SYSTEM "{PATH_TO_DOC}/language-defs.ent">
<!ENTITY % language-snippets.default SYSTEM "{PATH_TO_DOC}/language-snippets.ent">
<!ENTITY % extensions.default SYSTEM "{PATH_TO_DOC}/extensions.ent">
%language-defs.default;
%extensions.default;
%language-snippets.default;
<!-- All global entities for the XML files -->
<!ENTITY % global.entities SYSTEM "{PATH_TO_DOCBASE}/entities/global.ent">
<!-- These are language independent -->
<!ENTITY % frontpage.entities SYSTEM "{PATH_TO_DOC}/contributors.ent">
<!ENTITY % file.entities SYSTEM "{PATH_TO_DOCBASE}/entities/file-entities.ent">
<!-- Include all external DTD parts defined previously -->
%global.entities;
%file.entities;
%frontpage.entities;
]>
<book xml:id="book.fann" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xml:lang="en">
<title>Fann</title>
<titleabbrev>Fann</titleabbrev>
<preface xml:id="intro.fann">
&reftitle.intro;
<para>
</para>
</preface>
&reference.fann.setup;
&reference.fann.constants;
&reference.fann.examples;
&reference.fann.reference;
</book>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<book xml:id="book.fann" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<title>FANN (Fast Artificial Neural Network)</title>
<titleabbrev>FANN</titleabbrev>
<preface xml:id="intro.fann">
&reftitle.intro;
<para>
PHP binding for FANN Fast Artificial Neural Network) Library which implements multilayer
artificial neural networks with support for both fully connected and sparsely connected networks.
It includes a framework for easy handling of training data sets. It is easy to use, versatile,
well documented, and fast.
</para>
</preface>
&reference.fann.setup;
&reference.fann.constants;
&reference.fann.examples;
&reference.fann.reference;
&reference.fann.fannconnection;
</book>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<section xml:id="fann.installation" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
&reftitle.install;
<para>
&pecl.info;
<link xlink:href="&url.pecl.package;fann">&url.pecl.package;fann</link>
</para>
</section>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<appendix xml:id="fann.constants" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
&reftitle.constants;
&extension.constants;
<para>
<variablelist xml:id="constants.fann-train">
<title>Training algorithms</title>
<varlistentry xml:id="constant.fann-train-incremental">
<term>
<constant>FANN_TRAIN_INCREMENTAL</constant>
(<type>integer</type>)
</term>
<listitem>
<simpara>
Standard backpropagation algorithm, where the weights are updated after each training pattern.
This means that the weights are updated many times during a single epoch. For this reason some problems,
will train very fast with this algorithm, while other more advanced problems will not train very well.
</simpara>
</listitem>
</varlistentry>
<varlistentry xml:id="constant.fann-train-batch">
<term>
<constant>FANN_TRAIN_BATCH</constant>
(<type>integer</type>)
</term>
<listitem>
<simpara>
Standard backpropagation algorithm, where the weights are updated after calculating the mean square error
for the whole training set. This means that the weights are only updated once during a epoch.
For this reason some problems, will train slower with this algorithm. But since the mean square
error is calculated more correctly than in incremental training, some problems will reach a better
solutions with this algorithm.
</simpara>
</listitem>
</varlistentry>
<varlistentry xml:id="constant.fann-train-rprop">
<term>
<constant>FANN_TRAIN_RPROP</constant>
(<type>integer</type>)
</term>
<listitem>
<simpara>
A more advanced batch training algorithm which achieves good results for many problems. The RPROP
training algorithm is adaptive, and does therefore not use the learning_rate. Some other parameters
can however be set to change the way the RPROP algorithm works, but it is only recommended
for users with insight in how the RPROP training algorithm works. The RPROP training algorithm
is described by [Riedmiller and Braun, 1993], but the actual learning algorithm used here is
the iRPROP- training algorithm which is described by [Igel and Husken, 2000] which is an variety
of the standard RPROP training algorithm.
</simpara>
</listitem>
</varlistentry>
<varlistentry xml:id="constant.fann-train-quickprop">
<term>
<constant>FANN_TRAIN_QUICKPROP</constant>
(<type>integer</type>)
</term>
<listitem>
<simpara>
A more advanced batch training algorithm which achieves good results for many problems.
The quickprop training algorithm uses the learning_rate parameter along with other more advanced parameters,
but it is only recommended to change these advanced parameters, for users with insight in how the quickprop
training algorithm works. The quickprop training algorithm is described by [Fahlman, 1988].
</simpara>
</listitem>
</varlistentry>
<varlistentry xml:id="constant.fann-train-sarprop">
<term>
<constant>FANN_TRAIN_SARPROP</constant>
(<type>integer</type>)
</term>
<listitem>
<simpara>
Even more advance training algorithm. Only for version 2.2
</simpara>
</listitem>
</varlistentry>
</variablelist>
<variablelist xml:id="constants.fann-activation-funcs">
<title>Activation functions</title>
<varlistentry xml:id="constant.fann-linear">
<term>
<constant>FANN_LINEAR</constant>
(<type>integer</type>)
</term>
<listitem>
<simpara>
Linear activation function.
</simpara>
</listitem>
</varlistentry>
<varlistentry xml:id="constant.fann-threshold">
<term>
<constant>FANN_THRESHOLD</constant>
(<type>integer</type>)
</term>
<listitem>
<simpara>
Threshold activation function.
</simpara>
</listitem>
</varlistentry>
<varlistentry xml:id="constant.fann-threshold-symmetric">
<term>
<constant>FANN_THRESHOLD_SYMMETRIC</constant>
(<type>integer</type>)
</term>
<listitem>
<simpara>
Threshold activation function.
</simpara>
</listitem>
</varlistentry>
<varlistentry xml:id="constant.fann-sigmoid">
<term>
<constant>FANN_SIGMOID</constant>
(<type>integer</type>)
</term>
<listitem>
<simpara>
Sigmoid activation function.
</simpara>
</listitem>
</varlistentry>
<varlistentry xml:id="constant.fann-sigmoid-stepwise">
<term>
<constant>FANN_SIGMOID_STEPWISE</constant>
(<type>integer</type>)
</term>
<listitem>
<simpara>
Stepwise linear approximation to sigmoid.
</simpara>
</listitem>
</varlistentry>
<varlistentry xml:id="constant.fann-sigmoid-symmetric">
<term>
<constant>FANN_SIGMOID_SYMMETRIC</constant>
(<type>integer</type>)
</term>
<listitem>
<simpara>
Symmetric sigmoid activation function, aka. tanh.
</simpara>
</listitem>
</varlistentry>
<varlistentry xml:id="constant.fann-sigmoid-symmetric-stepwise">
<term>
<constant>FANN_SIGMOID_SYMMETRIC_STEPWISE</constant>
(<type>integer</type>)
</term>
<listitem>
<simpara>
Stepwise linear approximation to symmetric sigmoid
</simpara>
</listitem>
</varlistentry>
<varlistentry xml:id="constant.fann-gaussian">
<term>
<constant>FANN_GAUSSIAN</constant>
(<type>integer</type>)
</term>
<listitem>
<simpara>
Gaussian activation function.
</simpara>
</listitem>
</varlistentry>
<varlistentry xml:id="constant.fann-gaussian-symmetric">
<term>
<constant>FANN_GAUSSIAN_SYMMETRIC</constant>
(<type>integer</type>)
</term>
<listitem>
<simpara>
Symmetric gaussian activation function.
</simpara>
</listitem>
</varlistentry>
<varlistentry xml:id="constant.fann-gaussian-stepwise">
<term>
<constant>FANN_GAUSSIAN_STEPWISE</constant>
(<type>integer</type>)
</term>
<listitem>
<simpara>
Stepwise gaussian activation function.
</simpara>
</listitem>
</varlistentry>
<varlistentry xml:id="constant.fann-elliot">
<term>
<constant>FANN_ELLIOT</constant>
(<type>integer</type>)
</term>
<listitem>
<simpara>
Fast (sigmoid like) activation function defined by David Elliott.
</simpara>
</listitem>
</varlistentry>
<varlistentry xml:id="constant.fann-elliot-symmetric">
<term>
<constant>FANN_ELLIOT_SYMMETRIC</constant>
(<type>integer</type>)
</term>
<listitem>
<simpara>
Fast (symmetric sigmoid like) activation function defined by David Elliott.
</simpara>
</listitem>
</varlistentry>
<varlistentry xml:id="constant.fann-linear-piece">
<term>
<constant>FANN_LINEAR_PIECE</constant>
(<type>integer</type>)
</term>
<listitem>
<simpara>
Bounded linear activation function.
</simpara>
</listitem>
</varlistentry>
<varlistentry xml:id="constant.fann-linear-piece-symmetric">
<term>
<constant>FANN_LINEAR_PIECE_SYMMETRIC</constant>
(<type>integer</type>)
</term>
<listitem>
<simpara>
Bounded linear activation function.
</simpara>
</listitem>
</varlistentry>
<varlistentry xml:id="constant.fann-sin-symmetric">
<term>
<constant>FANN_SIN_SYMMETRIC</constant>
(<type>integer</type>)
</term>
<listitem>
<simpara>
Periodical sinus activation function.
</simpara>
</listitem>
</varlistentry>
<varlistentry xml:id="constant.fann-cos-symmetric">
<term>
<constant>FANN_COS_SYMMETRIC</constant>
(<type>integer</type>)
</term>
<listitem>
<simpara>
Periodical cosinus activation function.
</simpara>
</listitem>
</varlistentry>
<varlistentry xml:id="constant.fann-sin">
<term>
<constant>FANN_SIN</constant>
(<type>integer</type>)
</term>
<listitem>
<simpara>
Periodical sinus activation function.
</simpara>
</listitem>
</varlistentry>
<varlistentry xml:id="constant.fann-cos">
<term>
<constant>FANN_COS</constant>
(<type>integer</type>)
</term>
<listitem>
<simpara>
Periodical cosinus activation function.
</simpara>
</listitem>
</varlistentry>
</variablelist>
<variablelist xml:id="constants.fann-errorfunc">
<title>Error function used during training</title>
<varlistentry xml:id="constant.fann-errorfunc-linear">
<term>
<constant>FANN_ERRORFUNC_LINEAR</constant>
(<type>integer</type>)
</term>
<listitem>
<simpara>
Standard linear error function.
</simpara>
</listitem>
</varlistentry>
<varlistentry xml:id="constant.fann-errorfunc-tanh">
<term>
<constant>FANN_ERRORFUNC_TANH</constant>
(<type>integer</type>)
</term>
<listitem>
<simpara>
Tanh error function, usually better but can require a lower learning rate. This error function agressively
targets outputs that differ much from the desired, while not targetting outputs that only differ a little that much.
This activation function is not recommended for cascade training and incremental training.
</simpara>
</listitem>
</varlistentry>
</variablelist>
<variablelist xml:id="constants.fann-stopfunc">
<title>Stop criteria used during training</title>
<varlistentry xml:id="constant.fann-stopfunc-mse">
<term>
<constant>FANN_STOPFUNC_MSE</constant>
(<type>integer</type>)
</term>
<listitem>
<simpara>
Stop criteria is Mean Square Error (MSE) value.
</simpara>
</listitem>
</varlistentry>
<varlistentry xml:id="constant.fann-stopfunc-bit">
<term>
<constant>FANN_STOPFUNC_BIT</constant>
(<type>integer</type>)
</term>
<listitem>
<simpara>
Stop criteria is number of bits that fail. The number of bits means the number of output neurons
which differs more than the bit fail limit (see fann_get_bit_fail_limit, fann_set_bit_fail_limit). The bits are counted
in all of the training data, so this number can be higher than the number of training data.
</simpara>
</listitem>
</varlistentry>
</variablelist>
<variablelist xml:id="constants.fann-nettype">
<title>Definition of network types used by <function>fann_get_network_type</function></title>
<varlistentry xml:id="constant.fann-nettype-layer">
<term>
<constant>FANN_NETTYPE_LAYER</constant>
(<type>integer</type>)
</term>
<listitem>
<simpara>
Each layer only has connections to the next layer.
</simpara>
</listitem>
</varlistentry>
<varlistentry xml:id="constant.fann-nettype-shortcut">
<term>
<constant>FANN_NETTYPE_SHORTCUT</constant>
(<type>integer</type>)
</term>
<listitem>
<simpara>
Each layer has connections to all following layers
</simpara>
</listitem>
</varlistentry>
</variablelist>
<variablelist xml:id="constants.fann-e">
<title>Errors</title>
<varlistentry xml:id="constant.fann-e-no-error">
<term>
<constant>FANN_E_NO_ERROR</constant>
(<type>integer</type>)
</term>
<listitem>
<simpara>
No error.
</simpara>
</listitem>
</varlistentry>
<varlistentry xml:id="constant.fann-e-cant-open-config-r">
<term>
<constant>FANN_E_CANT_OPEN_CONFIG_R</constant>
(<type>integer</type>)
</term>
<listitem>
<simpara>
Unable to open configuration file for reading.
</simpara>
</listitem>
</varlistentry>
<varlistentry xml:id="constant.fann-e-cant-open-config-w">
<term>
<constant>FANN_E_CANT_OPEN_CONFIG_W</constant>
(<type>integer</type>)
</term>
<listitem>
<simpara>
Unable to open configuration file for writing.
</simpara>
</listitem>
</varlistentry>
<varlistentry xml:id="constant.fann-e-wrong-config-version">
<term>
<constant>FANN_E_WRONG_CONFIG_VERSION</constant>
(<type>integer</type>)
</term>
<listitem>
<simpara>
Wrong version of configuration file.
</simpara>
</listitem>
</varlistentry>
<varlistentry xml:id="constant.fann-e-cant-read-config">
<term>
<constant>FANN_E_CANT_READ_CONFIG</constant>
(<type>integer</type>)
</term>
<listitem>
<simpara>
Error reading info from configuration file.
</simpara>
</listitem>
</varlistentry>
<varlistentry xml:id="constant.fann-e-cant-read-neuron">
<term>
<constant>FANN_E_CANT_READ_NEURON</constant>
(<type>integer</type>)
</term>
<listitem>
<simpara>
Error reading neuron info from configuration file.
</simpara>
</listitem>
</varlistentry>
<varlistentry xml:id="constant.fann-e-cant-read-connections">
<term>
<constant>FANN_E_CANT_READ_CONNECTIONS</constant>
(<type>integer</type>)
</term>
<listitem>
<simpara>
Error reading connections from configuration file.
</simpara>
</listitem>
</varlistentry>
<varlistentry xml:id="constant.fann-e-wrong-num-connections">
<term>
<constant>FANN_E_WRONG_NUM_CONNECTIONS</constant>
(<type>integer</type>)
</term>
<listitem>
<simpara>
Number of connections not equal to the number expected.
</simpara>
</listitem>
</varlistentry>
<varlistentry xml:id="constant.fann-e-cant-open-td-w">
<term>
<constant>FANN_E_CANT_OPEN_TD_W</constant>
(<type>integer</type>)
</term>
<listitem>
<simpara>
Unable to open train data file for writing.
</simpara>
</listitem>
</varlistentry>
<varlistentry xml:id="constant.fann-e-cant-open-td-r">
<term>
<constant>FANN_E_CANT_OPEN_TD_R</constant>
(<type>integer</type>)
</term>
<listitem>
<simpara>
Unable to open train data file for reading.
</simpara>
</listitem>
</varlistentry>
<varlistentry xml:id="constant.fann-e-cant-read-td">
<term>
<constant>FANN_E_CANT_READ_TD</constant>
(<type>integer</type>)
</term>
<listitem>
<simpara>
Error reading training data from file.
</simpara>
</listitem>
</varlistentry>
<varlistentry xml:id="constant.fann-e-cant-allocate-mem">
<term>
<constant>FANN_E_CANT_ALLOCATE_MEM</constant>
(<type>integer</type>)
</term>
<listitem>
<simpara>
Unable to allocate memory.
</simpara>
</listitem>
</varlistentry>
<varlistentry xml:id="constant.fann-e-cant-train-activation">
<term>
<constant>FANN_E_CANT_TRAIN_ACTIVATION</constant>
(<type>integer</type>)
</term>
<listitem>
<simpara>
Unable to train with the selected activation function.
</simpara>
</listitem>
</varlistentry>
<varlistentry xml:id="constant.fann-e-cant-use-activation">
<term>
<constant>FANN_E_CANT_USE_ACTIVATION</constant>
(<type>integer</type>)
</term>
<listitem>
<simpara>
Unable to use the selected activation function.
</simpara>
</listitem>
</varlistentry>
<varlistentry xml:id="constant.fann-e-train-data-mismatch">
<term>
<constant>FANN_E_TRAIN_DATA_MISMATCH</constant>
(<type>integer</type>)
</term>
<listitem>
<simpara>
Irreconcilable differences between two struct fann_train_data structures.
</simpara>
</listitem>
</varlistentry>
<varlistentry xml:id="constant.fann-e-cant-use-train-alg">
<term>
<constant>FANN_E_CANT_USE_TRAIN_ALG</constant>
(<type>integer</type>)
</term>
<listitem>
<simpara>
Unable to use the selected training algorithm.
</simpara>
</listitem>
</varlistentry>
<varlistentry xml:id="constant.fann-e-train-data-subset">
<term>
<constant>FANN_E_TRAIN_DATA_SUBSET</constant>
(<type>integer</type>)
</term>
<listitem>
<simpara>
Trying to take subset which is not within the training set.
</simpara>
</listitem>
</varlistentry>
<varlistentry xml:id="constant.fann-e-index-out-of-bound">
<term>
<constant>FANN_E_INDEX_OUT_OF_BOUND</constant>
(<type>integer</type>)
</term>
<listitem>
<simpara>
Index is out of bound.
</simpara>
</listitem>
</varlistentry>
<varlistentry xml:id="constant.fann-e-scale-not-present">
<term>
<constant>FANN_E_SCALE_NOT_PRESENT</constant>
(<type>integer</type>)
</term>
<listitem>
<simpara>
Scaling parameters not present.
</simpara>
</listitem>
</varlistentry>
<varlistentry xml:id="constant.fann-e-input-no-match">
<term>
<constant>FANN_E_INPUT_NO_MATCH</constant>
(<type>integer</type>)
</term>
<listitem>
<simpara>
The number of input neurons in the ann data do not match
</simpara>
</listitem>
</varlistentry>
<varlistentry xml:id="constant.fann-e-output-no-match">
<term>
<constant>FANN_E_OUTPUT_NO_MATCH</constant>
(<type>integer</type>)
</term>
<listitem>
<simpara>
The number of output neurons in the ann and data do not match.
</simpara>
</listitem>
</varlistentry>
</variablelist>
</para>
</appendix>
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&reference.fann.fannconnection.construct;
&reference.fann.fannconnection.getfromneuron;
&reference.fann.fannconnection.gettoneuron;
&reference.fann.fannconnection.getweight;
&reference.fann.fannconnection.setweight;

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reference/fann/entities.functions.xml Normal file
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&reference.fann.functions.fann-cascadetrain-on-data;
&reference.fann.functions.fann-cascadetrain-on-file;
&reference.fann.functions.fann-clear-scaling-params;
&reference.fann.functions.fann-copy;
&reference.fann.functions.fann-create-from-file;
&reference.fann.functions.fann-create-shortcut-array;
&reference.fann.functions.fann-create-shortcut;
&reference.fann.functions.fann-create-sparse-array;
&reference.fann.functions.fann-create-sparse;
&reference.fann.functions.fann-create-standard-array;
&reference.fann.functions.fann-create-standard;
&reference.fann.functions.fann-create-train-from-callback;
&reference.fann.functions.fann-create-train;
&reference.fann.functions.fann-descale-input;
&reference.fann.functions.fann-descale-output;
&reference.fann.functions.fann-descale-train;
&reference.fann.functions.fann-destroy-train;
&reference.fann.functions.fann-destroy;
&reference.fann.functions.fann-duplicate-train-data;
&reference.fann.functions.fann-get-activation-function;
&reference.fann.functions.fann-get-activation-steepness;
&reference.fann.functions.fann-get-bias-array;
&reference.fann.functions.fann-get-bit-fail-limit;
&reference.fann.functions.fann-get-bit-fail;
&reference.fann.functions.fann-get-cascade-activation-functions-count;
&reference.fann.functions.fann-get-cascade-activation-functions;
&reference.fann.functions.fann-get-cascade-activation-steepnesses-count;
&reference.fann.functions.fann-get-cascade-activation-steepnesses;
&reference.fann.functions.fann-get-cascade-candidate-change-fraction;
&reference.fann.functions.fann-get-cascade-candidate-limit;
&reference.fann.functions.fann-get-cascade-candidate-stagnation-epochs;
&reference.fann.functions.fann-get-cascade-max-cand-epochs;
&reference.fann.functions.fann-get-cascade-max-out-epochs;
&reference.fann.functions.fann-get-cascade-min-cand-epochs;
&reference.fann.functions.fann-get-cascade-min-out-epochs;
&reference.fann.functions.fann-get-cascade-num-candidate-groups;
&reference.fann.functions.fann-get-cascade-num-candidates;
&reference.fann.functions.fann-get-cascade-output-change-fraction;
&reference.fann.functions.fann-get-cascade-output-stagnation-epochs;
&reference.fann.functions.fann-get-cascade-weight-multiplier;
&reference.fann.functions.fann-get-connection-array;
&reference.fann.functions.fann-get-connection-rate;
&reference.fann.functions.fann-get-errno;
&reference.fann.functions.fann-get-errstr;
&reference.fann.functions.fann-get-layer-array;
&reference.fann.functions.fann-get-learning-momentum;
&reference.fann.functions.fann-get-learning-rate;
&reference.fann.functions.fann-get-mse;
&reference.fann.functions.fann-get-network-type;
&reference.fann.functions.fann-get-num-input;
&reference.fann.functions.fann-get-num-layers;
&reference.fann.functions.fann-get-num-output;
&reference.fann.functions.fann-get-quickprop-decay;
&reference.fann.functions.fann-get-quickprop-mu;
&reference.fann.functions.fann-get-rprop-decrease-factor;
&reference.fann.functions.fann-get-rprop-delta-max;
&reference.fann.functions.fann-get-rprop-delta-min;
&reference.fann.functions.fann-get-rprop-delta-zero;
&reference.fann.functions.fann-get-rprop-increase-factor;
&reference.fann.functions.fann-get-sarprop-step-error-shift;
&reference.fann.functions.fann-get-sarprop-step-error-threshold-factor;
&reference.fann.functions.fann-get-sarprop-temperature;
&reference.fann.functions.fann-get-sarprop-weight-decay-shift;
&reference.fann.functions.fann-get-total-connections;
&reference.fann.functions.fann-get-total-neurons;
&reference.fann.functions.fann-get-train-error-function;
&reference.fann.functions.fann-get-train-stop-function;
&reference.fann.functions.fann-get-training-algorithm;
&reference.fann.functions.fann-init-weights;
&reference.fann.functions.fann-length-train-data;
&reference.fann.functions.fann-merge-train-data;
&reference.fann.functions.fann-num-input-train-data;
&reference.fann.functions.fann-num-output-train-data;
&reference.fann.functions.fann-print-error;
&reference.fann.functions.fann-randomize-weights;
&reference.fann.functions.fann-read-train-from-file;
&reference.fann.functions.fann-reset-errno;
&reference.fann.functions.fann-reset-errstr;
&reference.fann.functions.fann-reset-mse;
&reference.fann.functions.fann-run;
&reference.fann.functions.fann-save-train;
&reference.fann.functions.fann-save;
&reference.fann.functions.fann-scale-input-train-data;
&reference.fann.functions.fann-scale-input;
&reference.fann.functions.fann-scale-output-train-data;
&reference.fann.functions.fann-scale-output;
&reference.fann.functions.fann-scale-train-data;
&reference.fann.functions.fann-scale-train;
&reference.fann.functions.fann-set-activation-function-hidden;
&reference.fann.functions.fann-set-activation-function-layer;
&reference.fann.functions.fann-set-activation-function-output;
&reference.fann.functions.fann-set-activation-function;
&reference.fann.functions.fann-set-activation-steepness-hidden;
&reference.fann.functions.fann-set-activation-steepness-layer;
&reference.fann.functions.fann-set-activation-steepness-output;
&reference.fann.functions.fann-set-activation-steepness;
&reference.fann.functions.fann-set-bit-fail-limit;
&reference.fann.functions.fann-set-callback;
&reference.fann.functions.fann-set-cascade-activation-functions;
&reference.fann.functions.fann-set-cascade-activation-steepnesses;
&reference.fann.functions.fann-set-cascade-candidate-change-fraction;
&reference.fann.functions.fann-set-cascade-candidate-limit;
&reference.fann.functions.fann-set-cascade-candidate-stagnation-epochs;
&reference.fann.functions.fann-set-cascade-max-cand-epochs;
&reference.fann.functions.fann-set-cascade-max-out-epochs;
&reference.fann.functions.fann-set-cascade-min-cand-epochs;
&reference.fann.functions.fann-set-cascade-min-out-epochs;
&reference.fann.functions.fann-set-cascade-num-candidate-groups;
&reference.fann.functions.fann-set-cascade-output-change-fraction;
&reference.fann.functions.fann-set-cascade-output-stagnation-epochs;
&reference.fann.functions.fann-set-cascade-weight-multiplier;
&reference.fann.functions.fann-set-error-log;
&reference.fann.functions.fann-set-input-scaling-params;
&reference.fann.functions.fann-set-learning-momentum;
&reference.fann.functions.fann-set-learning-rate;
&reference.fann.functions.fann-set-output-scaling-params;
&reference.fann.functions.fann-set-quickprop-decay;
&reference.fann.functions.fann-set-quickprop-mu;
&reference.fann.functions.fann-set-rprop-decrease-factor;
&reference.fann.functions.fann-set-rprop-delta-max;
&reference.fann.functions.fann-set-rprop-delta-min;
&reference.fann.functions.fann-set-rprop-delta-zero;
&reference.fann.functions.fann-set-rprop-increase-factor;
&reference.fann.functions.fann-set-sarprop-step-error-shift;
&reference.fann.functions.fann-set-sarprop-step-error-threshold-factor;
&reference.fann.functions.fann-set-sarprop-temperature;
&reference.fann.functions.fann-set-sarprop-weight-decay-shift;
&reference.fann.functions.fann-set-scaling-params;
&reference.fann.functions.fann-set-train-error-function;
&reference.fann.functions.fann-set-train-stop-function;
&reference.fann.functions.fann-set-training-algorithm;
&reference.fann.functions.fann-set-weight-array;
&reference.fann.functions.fann-set-weight;
&reference.fann.functions.fann-shuffle-train-data;
&reference.fann.functions.fann-subset-train-data;
&reference.fann.functions.fann-test-data;
&reference.fann.functions.fann-test;
&reference.fann.functions.fann-train-epoch;
&reference.fann.functions.fann-train-on-data;
&reference.fann.functions.fann-train-on-file;
&reference.fann.functions.fann-train;

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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<chapter xml:id="fann.examples" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
&reftitle.examples;
<section xml:id="fann.examples-1">
<title>XOR training</title>
<para>
This example shows how to train data for XOR function
<example>
<title>Simple train</title>
<programlisting role="php">
<![CDATA[
<?php
$num_input = 2;
$num_output = 1;
$num_layers = 3;
$num_neurons_hidden = 3;
$desired_error = 0.001;
$max_epochs = 500000;
$epochs_between_reports = 1000;
$ann = fann_create_standard($num_layers, $num_input, $num_neurons_hidden, $num_output);
if ($ann) {
fann_set_activation_function_hidden($ann, FANN_SIGMOID_SYMMETRIC);
fann_set_activation_function_output($ann, FANN_SIGMOID_SYMMETRIC);
$filename = dirname(__FILE__) . "/xor.data";
if (fann_train_on_file($ann, $filename, $max_epochs, $epochs_between_reports, $desired_error))
fann_save($ann, dirname(__FILE__) . "/xor_float.net");
fann_destroy($ann);
}
?>
]]>
</programlisting>
</example>
</para>
<para>
This example shows how to read and run data for XOR function
<example>
<title>Simple test</title>
<programlisting role="php">
<![CDATA[
<?php
$train_file = (dirname(__FILE__) . "/xor_float.net");
if (!is_file($train_file))
die("The file xor_float.net has not been created! Please run simple_train.php to generate it");
$ann = fann_create_from_file($train_file);
if (!$ann)
die("ANN could not be created");
$input = array(-1, 1);
$calc_out = fann_run($ann, $input);
printf("xor test (%f,%f) -> %f\n", $input[0], $input[1], $calc_out[0]);
fann_destroy($ann);
?>
]]>
</programlisting>
</example>
</para>
</section>
</chapter>

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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<phpdoc:classref xml:id="class.fannconnection" xmlns:phpdoc="http://php.net/ns/phpdoc" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xi="http://www.w3.org/2001/XInclude">
<title>The FANNConnection class</title>
<titleabbrev>FANNConnection</titleabbrev>
<partintro>
<!-- {{{ FANNConnection intro -->
<section xml:id="fannconnection.intro">
&reftitle.intro;
<para>
<classname>FANNConnection</classname> is used for the neural network connection.
The objects of this class are used in <function>fann_get_connection_array</function> and <function>fann_set_weight_array</function>.
</para>
</section>
<!-- }}} -->
<section xml:id="fannconnection.synopsis">
&reftitle.classsynopsis;
<!-- {{{ Synopsis -->
<classsynopsis>
<ooclass><classname>FANNConnection</classname></ooclass>
<!-- {{{ Class synopsis -->
<classsynopsisinfo>
<ooclass>
<classname>FANNConnection</classname>
</ooclass>
</classsynopsisinfo>
<!-- }}} -->
<classsynopsisinfo role="comment">&Properties;</classsynopsisinfo>
<fieldsynopsis>
<modifier>public</modifier>
<varname linkend="fannconnection.props.from-neuron">from_neuron</varname>
</fieldsynopsis>
<fieldsynopsis>
<modifier>public</modifier>
<varname linkend="fannconnection.props.to-neuron">to_neuron</varname>
</fieldsynopsis>
<fieldsynopsis>
<modifier>public</modifier>
<varname linkend="fannconnection.props.weight">weight</varname>
</fieldsynopsis>
<classsynopsisinfo role="comment">&Methods;</classsynopsisinfo>
<xi:include xpointer="xmlns(db=http://docbook.org/ns/docbook) xpointer(id('class.fannconnection')/db:refentry/db:refsect1[@role='description']/descendant::db:methodsynopsis[1])" />
</classsynopsis>
<!-- }}} -->
</section>
<!-- {{{ FANNConnection properties -->
<section xml:id="fannconnection.props">
&reftitle.properties;
<variablelist>
<varlistentry xml:id="fannconnection.props.from-neuron">
<term><varname>from_neuron</varname></term>
<listitem>
<para>The neuron where the connection starts.</para>
</listitem>
</varlistentry>
<varlistentry xml:id="fannconnection.props.to-neuron">
<term><varname>to_neuron</varname></term>
<listitem>
<para>The neuron where the connection ends.</para>
</listitem>
</varlistentry>
<varlistentry xml:id="fannconnection.props.weight">
<term><varname>weight</varname></term>
<listitem>
<para>The weight of the connection.</para>
</listitem>
</varlistentry>
</variablelist>
</section>
<!-- }}} -->
</partintro>
&reference.fann.entities.fannconnection;
</phpdoc:classref>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="fannconnection.construct" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>FANNConnection::__construct</refname>
<refpurpose>The connection constructor</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<modifier>public</modifier> <methodname>FANNConnection::__construct</methodname>
<methodparam><type>int</type><parameter>from_neuron</parameter></methodparam>
<methodparam><type>int</type><parameter>to_neuron</parameter></methodparam>
<methodparam><type>float</type><parameter>weight</parameter></methodparam>
</methodsynopsis>
<para>
Create new connection and initialize its params. After creating the connection, only weight can be changed.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>from_neuron</parameter></term>
<listitem>
<para>
The postion number of starting neuron.
</para>
</listitem>
</varlistentry>
<varlistentry>
<term><parameter>to_neuron</parameter></term>
<listitem>
<para>
The postion number of terminating neuron.
</para>
</listitem>
</varlistentry>
<varlistentry>
<term><parameter>weight</parameter></term>
<listitem>
<para>
The connection weight value.
</para>
</listitem>
</varlistentry>
</variablelist>
</refsect1>
</refentry>
<!-- Keep this comment at the end of the file
Local variables:
mode: sgml
sgml-omittag:t
sgml-shorttag:t
sgml-minimize-attributes:nil
sgml-always-quote-attributes:t
sgml-indent-step:1
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="fannconnection.getfromneuron" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>FANNConnection::getFromNeuron</refname>
<refpurpose>Returns the postions of starting neuron.</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<modifier>public</modifier> <type>int</type><methodname>FANNConnection::getFromNeuron</methodname>
<void />
</methodsynopsis>
<para>
Returns the postions of starting neuron.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
&no.function.parameters;
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
The postions of starting neuron.
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="fannconnection.gettoneuron" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>FANNConnection::getToNeuron</refname>
<refpurpose>Returns the postions of terminating neuron</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<modifier>public</modifier> <type>int</type><methodname>FANNConnection::getToNeuron</methodname>
<void />
</methodsynopsis>
<para>
Returns the postions of terminating neuron.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
&no.function.parameters;
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
The postions of terminating neuron.
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="fannconnection.getweight" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>FANNConnection::getWeight</refname>
<refpurpose>Returns the connection weight</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<modifier>public</modifier> <type>void</type><methodname>FANNConnection::getWeight</methodname>
<void />
</methodsynopsis>
<para>
Returns the connection weight.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
&no.function.parameters;
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
The connection weight.
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="fannconnection.setweight" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>FANNConnection::setWeight</refname>
<refpurpose>Sets the connections weight</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<modifier>public</modifier> <type>bool</type><methodname>FANNConnection::setWeight</methodname>
<methodparam><type>float</type><parameter>weight</parameter></methodparam>
</methodsynopsis>
<para>
Sets the connection weight.
</para>
<para>
This method is different than <function>fann_set_weight</function>. It does not
update the weight value in the network. The network value is updated only after calling
<function>fann_set_weight_array</function>.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<para>
<variablelist>
<varlistentry>
<term><parameter>weight</parameter></term>
<listitem>
<para>
The connection weight.
</para>
</listitem>
</varlistentry>
</variablelist>
</para>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
&fann.return.bool;
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-cascadetrain-on-data" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_cascadetrain_on_data</refname>
<refpurpose>Trains on an entire dataset, for a period of time using the Cascade2 training algorithm</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>bool</type><methodname>fann_cascadetrain_on_data</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
<methodparam><type>resource</type><parameter>data</parameter></methodparam>
<methodparam><type>int</type><parameter>max_neurons</parameter></methodparam>
<methodparam><type>int</type><parameter>neurons_between_reports</parameter></methodparam>
<methodparam><type>float</type><parameter>desired_error</parameter></methodparam>
</methodsynopsis>
<para>
The cascade output change fraction is a number between 0 and 1 determining how large a fraction
the <function>fann_get_MSE</function> value should change within <function>fann_get_cascade_output_stagnation_epochs</function>
during training of the output connections, in order for the training not to stagnate. If the training stagnates,
the training of the output connections will be ended and new candidates will be prepared.
</para>
<para>
This training uses the parameters set using the fann_set_cascade_..., but it also uses another training algorithm
as it’s internal training algorithm. This algorithm can be set to either <constant>FANN_TRAIN_RPROP</constant> or
<constant>FANN_TRAIN_QUICKPROP</constant> by <function>fann_set_training_algorithm</function>, and the parameters
set for these training algorithms will also affect the cascade training.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
<varlistentry>
<term><parameter>data</parameter></term>
<listitem>
&fann.train.description;
</listitem>
</varlistentry>
<varlistentry>
<term><parameter>max_neurons</parameter></term>
<listitem>
<para>
The maximum number of neurons to be added to neural network.
</para>
</listitem>
</varlistentry>
<varlistentry>
<term><parameter>neurons_between_reports</parameter></term>
<listitem>
<para>
The number of neurons between printing a status report. A value of zero means no reports should be printed.
</para>
</listitem>
</varlistentry>
<varlistentry>
<term><parameter>desired_error</parameter></term>
<listitem>
<para>
The desired <function>fann_get_MSE</function> or <function>fann_get_bit_fail</function>,
depending on which stop function is chosen by <function>fann_set_train_stop_function</function>
</para>
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
&fann.return.bool;
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_train_on_data</function></member>
<member><function>fann_cascadetrain_on_file</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-cascadetrain-on-file" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_cascadetrain_on_file</refname>
<refpurpose>Trains on an entire dataset read from file, for a period of time using the Cascade2 training algorithm.</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>bool</type><methodname>fann_cascadetrain_on_file</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
<methodparam><type>string</type><parameter>filename</parameter></methodparam>
<methodparam><type>int</type><parameter>max_neurons</parameter></methodparam>
<methodparam><type>int</type><parameter>neurons_between_reports</parameter></methodparam>
<methodparam><type>float</type><parameter>desired_error</parameter></methodparam>
</methodsynopsis>
<para>
Does the same as <function>fann_cascadetrain_on_data</function>, but reads the training data directly from a file.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
<varlistentry>
<term><parameter>filename</parameter></term>
<listitem>
<para>
The maximum number of neurons to be added to neural network
</para>
</listitem>
</varlistentry>
<varlistentry>
<term><parameter>max_neurons</parameter></term>
<listitem>
<para>
The number of neurons between printing a status report to stdout.
A value of zero means no reports should be printed.
</para>
</listitem>
</varlistentry>
<varlistentry>
<term><parameter>neurons_between_reports</parameter></term>
<listitem>
<para>
The number of neurons between printing a status report. A value of zero means no reports should be printed.
</para>
</listitem>
</varlistentry>
<varlistentry>
<term><parameter>desired_error</parameter></term>
<listitem>
<para>
The desired <function>fann_get_MSE</function> or <function>fann_get_bit_fail</function>,
depending on which stop function is chosen by <function>fann_set_train_stop_function</function>.
</para>
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
&fann.return.bool;
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_train_on_data</function></member>
<member><function>fann_cascadetrain_on_data</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-clear-scaling-params" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_clear_scaling_params</refname>
<refpurpose>Clears scaling parameters</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>bool</type><methodname>fann_clear_scaling_params</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
</methodsynopsis>
<para>
Clears scaling parameters.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
&fann.return.bool;
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-copy" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_copy</refname>
<refpurpose>Creates a copy of a fann structure</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>resource</type><methodname>fann_copy</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
</methodsynopsis>
<para>
Creates a copy of a fann structure.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
Returns a copy of neural network resource on success, or &false; on error
</para>
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_test</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-create-from-file" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_create_from_file</refname>
<refpurpose>Constructs a backpropagation neural network from a configuration file</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>resource</type><methodname>fann_create_from_file</methodname>
<methodparam><type>string</type><parameter>configuration_file</parameter></methodparam>
</methodsynopsis>
<para>
Constructs a backpropagation neural network from a configuration file, which have been saved by <function>fann_save</function>.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>configuration_file</parameter></term>
<listitem>
<para>
The configuration file path.
</para>
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
&fann.return.ann;
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_save</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-create-shortcut-array" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_create_shortcut_array</refname>
<refpurpose>Creates a standard backpropagation neural network which is not fully connectected and has shortcut connections</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>resource</type><methodname>fann_create_shortcut_array</methodname>
<methodparam><type>int</type><parameter>num_layers</parameter></methodparam>
<methodparam><type>array</type><parameter>layers</parameter></methodparam>
</methodsynopsis>
<para>
Creates a standard backpropagation neural network which is not fully connectected and has shortcut connections using an array of layers sizes.
</para>
&warn.undocumented.func;
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>num_layers</parameter></term>
<listitem>
<para>
The total number of layers including the input and the output layer.
</para>
</listitem>
</varlistentry>
<varlistentry>
<term><parameter>layers</parameter></term>
<listitem>
<para>
An array of layers sizes.
</para>
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
Returns a neural network resource on success, or &false; on error.
</para>
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_create_shortcut</function></member>
<member><function>fann_create_sparse</function></member>
<member><function>fann_create_standard</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-create-shortcut" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_create_shortcut</refname>
<refpurpose>Creates a standard backpropagation neural network which is not fully connectected and has shortcut connections</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>reference</type><methodname>fann_create_shortcut</methodname>
<methodparam><type>int</type><parameter>num_layers</parameter></methodparam>
<methodparam><type>int</type><parameter>num_neurons1</parameter></methodparam>
<methodparam><type>int</type><parameter>num_neurons2</parameter></methodparam>
<methodparam choice="opt"><type>int</type><parameter>...</parameter></methodparam>
</methodsynopsis>
<para>
Creates a standard backpropagation neural network, which is not fully connected and which also has shortcut connections.
</para>
<para>
Shortcut connections are connections that skip layers. A fully connected network with shortcut connections, is a network
where all neurons are connected to all neurons in later layers. Including direct connections from the input layer to the output layer.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>num_layers</parameter></term>
<listitem>
<para>
The total number of layers including the input and the output layer.
</para>
</listitem>
</varlistentry>
<varlistentry>
<term><parameter>num_neurons1</parameter></term>
<listitem>
<para>
Number of neurons in the first layer.
</para>
</listitem>
</varlistentry>
<varlistentry>
<term><parameter>num_neurons2</parameter></term>
<listitem>
<para>
Number of neurons in the second layer.
</para>
</listitem>
</varlistentry>
<varlistentry>
<term><parameter>...</parameter></term>
<listitem>
<para>
Number of neurons in other layers.
</para>
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
Returns a neural network resource on success, or &false; on error.
</para>
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_create_shortcut_array</function></member>
<member><function>fann_create_sparse</function></member>
<member><function>fann_create_standard</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-create-sparse-array" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_create_sparse_array</refname>
<refpurpose>Creates a standard backpropagation neural network, which is not fully connected using an array of layer sizes</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>ReturnType</type><methodname>fann_create_sparse_array</methodname>
<methodparam><type>float</type><parameter>connection_rate</parameter></methodparam>
<methodparam><type>int</type><parameter>num_layers</parameter></methodparam>
<methodparam><type>array</type><parameter>layers</parameter></methodparam>
</methodsynopsis>
<para>
Creates a standard backpropagation neural network, which is not fully connected using an array of layer sizes.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>connection_rate</parameter></term>
<listitem>
<para>
The connection rate controls how many connections there will be in the network. If the connection rate
is set to 1, the network will be fully connected, but if it is set to 0.5 only half of the connections
will be set. A connection rate of 1 will yield the same result as <function>fann_create_standard</function>.
</para>
</listitem>
</varlistentry>
<varlistentry>
<term><parameter>num_layers</parameter></term>
<listitem>
<para>
The total number of layers including the input and the output layer.
</para>
</listitem>
</varlistentry>
<varlistentry>
<term><parameter>layers</parameter></term>
<listitem>
<para>
An array of layer sizes.
</para>
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
Returns a neural network resource on success, or &false; on error.
</para>
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_create_sparse</function></member>
<member><function>fann_create_standard</function></member>
<member><function>fann_create_shortcut</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-create-sparse" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_create_sparse</refname>
<refpurpose>Creates a standard backpropagation neural network, which is not fully connected</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>ReturnType</type><methodname>fann_create_sparse</methodname>
<methodparam><type>float</type><parameter>connection_rate</parameter></methodparam>
<methodparam><type>int</type><parameter>num_layers</parameter></methodparam>
<methodparam><type>int</type><parameter>num_neurons1</parameter></methodparam>
<methodparam><type>int</type><parameter>num_neurons2</parameter></methodparam>
<methodparam choice="opt"><type>int</type><parameter>...</parameter></methodparam>
</methodsynopsis>
<para>
Creates a standard backpropagation neural network, which is not fully connected.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>connection_rate</parameter></term>
<listitem>
<para>
The connection rate controls how many connections there will be in the network. If the connection rate
is set to 1, the network will be fully connected, but if it is set to 0.5 only half of the connections
will be set. A connection rate of 1 will yield the same result as <function>fann_create_standard</function>.
</para>
</listitem>
</varlistentry>
<varlistentry>
<term><parameter>num_layers</parameter></term>
<listitem>
<para>
The total number of layers including the input and the output layer.
</para>
</listitem>
</varlistentry>
<varlistentry>
<term><parameter>num_neurons1</parameter></term>
<listitem>
<para>
Number of neurons in the first layer.
</para>
</listitem>
</varlistentry>
<varlistentry>
<term><parameter>num_neurons2</parameter></term>
<listitem>
<para>
Number of neurons in the second layer.
</para>
</listitem>
</varlistentry>
<varlistentry>
<term><parameter>...</parameter></term>
<listitem>
<para>
Number of neurons in other layers.
</para>
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
Returns a neural network resource on success, or &false; on error.
</para>
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_create_sparse_array</function></member>
<member><function>fann_create_standard</function></member>
<member><function>fann_create_shortcut</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-create-standard-array" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_create_standard_array</refname>
<refpurpose>Creates a standard fully connected backpropagation neural network using an array of layer sizes</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>resource</type><methodname>fann_create_standard_array</methodname>
<methodparam><type>int</type><parameter>num_layers</parameter></methodparam>
<methodparam><type>array</type><parameter>layers</parameter></methodparam>
</methodsynopsis>
<para>
Creates a standard fully connected backpropagation neural network.
</para>
<para>
There will be a bias neuron in each layer (except the output layer),
and this bias neuron will be connected to all neurons in the next layer.
When running the network, the bias nodes always emits 1.
</para>
<para>
To destroy a neural network use the <function>fann_destroy</function> function.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>num_layers</parameter></term>
<listitem>
<para>
The total number of layers including the input and the output layer.
</para>
</listitem>
</varlistentry>
<varlistentry>
<term><parameter>layers</parameter></term>
<listitem>
<para>
An array of layer sizes.
</para>
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
Returns a neural network resource on success, or &false; on error.
</para>
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_create_standard</function></member>
<member><function>fann_create_sparse</function></member>
<member><function>fann_create_shortcut</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-create-standard" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_create_standard</refname>
<refpurpose>Creates a standard fully connected backpropagation neural network</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>resource</type><methodname>fann_create_standard</methodname>
<methodparam><type>int</type><parameter>num_layers</parameter></methodparam>
<methodparam><type>int</type><parameter>num_neurons1</parameter></methodparam>
<methodparam><type>int</type><parameter>num_neurons2</parameter></methodparam>
<methodparam choice="opt"><type>int</type><parameter>...</parameter></methodparam>
</methodsynopsis>
<para>
Creates a standard fully connected backpropagation neural network.
</para>
<para>
There will be a bias neuron in each layer (except the output layer),
and this bias neuron will be connected to all neurons in the next layer.
When running the network, the bias nodes always emits 1.
</para>
<para>
To destroy a neural network use the <function>fann_destroy</function> function.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>num_layers</parameter></term>
<listitem>
<para>
The total number of layers including the input and the output layer.
</para>
</listitem>
</varlistentry>
<varlistentry>
<term><parameter>num_neurons1</parameter></term>
<listitem>
<para>
Number of neurons in the first layer.
</para>
</listitem>
</varlistentry>
<varlistentry>
<term><parameter>num_neurons2</parameter></term>
<listitem>
<para>
Number of neurons in the second layer.
</para>
</listitem>
</varlistentry>
<varlistentry>
<term><parameter>...</parameter></term>
<listitem>
<para>
Number of neurons in other layers.
</para>
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
Returns a neural network resource on success, or &false; on error.
</para>
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_create_standard_array</function></member>
<member><function>fann_create_sparse</function></member>
<member><function>fann_create_shortcut</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
<!-- Keep this comment at the end of the file
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sgml-local-catalogs:nil
sgml-local-ecat-files:nil
End:
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-create-train-from-callback" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_create_train_from_callback</refname>
<refpurpose>Creates the training data struct from a user supplied function</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>resource</type><methodname>fann_create_train_from_callback</methodname>
<methodparam><type>int</type><parameter>num_data</parameter></methodparam>
<methodparam><type>int</type><parameter>num_input</parameter></methodparam>
<methodparam><type>int</type><parameter>num_output</parameter></methodparam>
<methodparam><type>collable</type><parameter>user_function</parameter></methodparam>
</methodsynopsis>
<para>
Creates the training data struct from a user supplied function. As the training data are numerable (data 1, data 2...),
the user must write a function that receives the number of the training data set (input, output) and returns the set.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>num_data</parameter></term>
<listitem>
<para>
The number of training data
</para>
</listitem>
</varlistentry>
<varlistentry>
<term><parameter>num_input</parameter></term>
<listitem>
<para>
The number of inputs per training data
</para>
</listitem>
</varlistentry>
<varlistentry>
<term><parameter>num_output</parameter></term>
<listitem>
<para>
The number of ouputs per training data
</para>
</listitem>
</varlistentry>
<varlistentry>
<term><parameter>user_function</parameter></term>
<listitem>
<para>
The user supplied function with following parameters:
<simplelist>
<member><literal>num</literal> - The number of the training data set</member>
<member><literal>num_input</literal> - The number of inputs per training data</member>
<member><literal>num</literal> - The number of ouputs per training dataThe number of inputs per training data</member>
</simplelist>
</para>
<para>
The function should return an associative array with keys <literal>input</literal> and <literal>output</literal> and
two array values of input and output.
</para>
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
&fann.return.train;
</refsect1>
<refsect1 role="examples">
&reftitle.examples;
<para>
<example>
<title><methodname>fann_create_train_from_callback</methodname> example</title>
<programlisting role="php">
<![CDATA[
<?php
function create_train_callback($num_data, $num_input, $num_output) {
return array(
"input" => array_fill(0, $num_input, 1),
"output" => array_fill(0, $num_output, 1),
);
}
$num_data = 3;
$num_input = 2;
$num_output = 1;
$train_data = fann_create_train_from_callback($num_data, $num_input, $num_output, "create_train_callback");
if ($train_data) {
// Do something with $train_data
}
?>
]]>
</programlisting>
</example>
</para>
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_read_train_from_file</function></member>
<member><function>fann_train_on_data</function></member>
<member><function>fann_destroy_train</function></member>
<member><function>fann_save_train</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
<!-- Keep this comment at the end of the file
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-create-train" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_create_train</refname>
<refpurpose>Creates an empty training data struct</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>resource</type><methodname>fann_create_train</methodname>
<methodparam><type>int</type><parameter>num_data</parameter></methodparam>
<methodparam><type>int</type><parameter>num_input</parameter></methodparam>
<methodparam><type>int</type><parameter>num_output</parameter></methodparam>
</methodsynopsis>
<para>
Creates an empty training data struct.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>num_data</parameter></term>
<listitem>
<para>
The number of training data
</para>
</listitem>
</varlistentry>
<varlistentry>
<term><parameter>num_input</parameter></term>
<listitem>
<para>
The number of inputs per training data
</para>
</listitem>
</varlistentry>
<varlistentry>
<term><parameter>num_output</parameter></term>
<listitem>
<para>
The number of ouputs per training data
</para>
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
&fann.return.train;
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_read_train_from_file</function></member>
<member><function>fann_train_on_data</function></member>
<member><function>fann_destroy_train</function></member>
<member><function>fann_save_train</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-descale-input" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_descale_input</refname>
<refpurpose>Scale data in input vector after get it from ann based on previously calculated parameters</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>bool</type><methodname>fann_descale_input</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
<methodparam><type>array</type><parameter>input_vector</parameter></methodparam>
</methodsynopsis>
<para>
Scale data in input vector after get it from ann based on previously calculated parameters.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
<varlistentry>
<term><parameter>input_vector</parameter></term>
<listitem>
<para>
Input vector that will be descaled
</para>
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
&fann.return.bool;
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_scale_input</function></member>
<member><function>fann_descale_output</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-descale-output" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_descale_output</refname>
<refpurpose>Scale data in output vector after get it from ann based on previously calculated parameters</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>bool</type><methodname>fann_descale_output</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
<methodparam><type>array</type><parameter>output_vector</parameter></methodparam>
</methodsynopsis>
<para>
Scale data in output vector after get it from ann based on previously calculated parameters.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
<varlistentry>
<term><parameter>output_vector</parameter></term>
<listitem>
<para>
Output vector that will be descaled
</para>
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
&fann.return.bool;
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_scale_output</function></member>
<member><function>fann_descale_input</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-descale-train" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_descale_train</refname>
<refpurpose>Descale input and output data based on previously calculated parameters</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>bool</type><methodname>fann_descale_train</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
<methodparam><type>resource</type><parameter>train_data</parameter></methodparam>
</methodsynopsis>
<para>
Descale input and output data based on previously calculated parameters.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
<varlistentry>
<term><parameter>train_data</parameter></term>
<listitem>
&fann.train.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
&fann.return.bool;
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_scale_train</function></member>
<member><function>fann_set_scaling_params</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-destroy-train" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_destroy_train</refname>
<refpurpose>Destructs the training data</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>bool</type><methodname>fann_destroy_train</methodname>
<methodparam><type>resource</type><parameter>train_data</parameter></methodparam>
</methodsynopsis>
<para>
Destructs the training data
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>train_data</parameter></term>
<listitem>
&fann.train.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
&fann.return.bool;
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-destroy" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_destroy</refname>
<refpurpose>Destroys the entire network and properly freeing all the associated memory</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>bool</type><methodname>fann_destroy</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
</methodsynopsis>
<para>
Destroys the entire network and properly freeing all the associated memory.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
&fann.return.bool;
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-duplicate-train-data" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_duplicate_train_data</refname>
<refpurpose>Returns an exact copy of a fann train data</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>resource</type><methodname>fann_duplicate_train_data</methodname>
<methodparam><type>resource</type><parameter>data</parameter></methodparam>
</methodsynopsis>
<para>
Returns an exact copy of a fann train data <type>resource</type>.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>data</parameter></term>
<listitem>
&fann.train.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
&fann.return.train;
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-get-activation-function" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_get_activation_function</refname>
<refpurpose>Returns the activation function</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>int</type><methodname>fann_get_activation_function</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
<methodparam><type>int</type><parameter>layer</parameter></methodparam>
<methodparam><type>int</type><parameter>neuron</parameter></methodparam>
</methodsynopsis>
<para>
Get the activation function for neuron number <literal>neuron</literal> in layer number
<literal>layer</literal>, counting the input layer as layer 0.
</para>
<para>
It is not possible to get activation functions for the neurons in the input layer.
</para>
<para>
The return value is one of the <link linkend="constants.fann-activation-funcs">activation functions</link> constants.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
<varlistentry>
<term><parameter>layer</parameter></term>
<listitem>
<para>
Layer number.
</para>
</listitem>
</varlistentry>
<varlistentry>
<term><parameter>neuron</parameter></term>
<listitem>
<para>
Neuron number.
</para>
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
<link linkend="constants.fann-train">Learning functions</link> constant or -1
if the neuron is not defined in the neural network, or &false; on error.
</para>
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_set_activation_function_layer</function></member>
<member><function>fann_set_activation_function_hidden</function></member>
<member><function>fann_set_activation_function_output</function></member>
<member><function>fann_set_activation_steepness</function></member>
<member><function>fann_set_activation_function</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-get-activation-steepness" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_get_activation_steepness</refname>
<refpurpose>Returns the activation steepness for supplied neuron and layer number</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>float</type><methodname>fann_get_activation_steepness</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
<methodparam><type>int</type><parameter>layer</parameter></methodparam>
<methodparam><type>int</type><parameter>neuron</parameter></methodparam>
</methodsynopsis>
<para>
Get the activation steepness for neuron number <literal>neuron</literal> in layer number
<literal>layer</literal>, counting the input layer as layer 0.
</para>
<para>
It is not possible to get activation steepness for the neurons in the input layer.
</para>
<para>
The steepness of an activation function says something about how fast the activation function goes
from the minimum to the maximum. A high value for the activation function will also give a more agressive training.
</para>
<para>
When training neural networks where the output values should be at the extremes
(usually 0 and 1, depending on the activation function), a steep activation function can be used (e.g. 1.0).
</para>
<para>
The default activation steepness is 0.5.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
<varlistentry>
<term><parameter>layer</parameter></term>
<listitem>
<para>
Layer number
</para>
</listitem>
</varlistentry>
<varlistentry>
<term><parameter>neuron</parameter></term>
<listitem>
<para>
Neuron number
</para>
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
The activation steepness for the neuron or -1 if the neuron is not defined in the neural network, or &false; on error.
</para>
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_set_activation_function</function></member>
<member><function>fann_set_activation_steepness_layer</function></member>
<member><function>fann_set_activation_steepness_hidden</function></member>
<member><function>fann_set_activation_steepness_output</function></member>
<member><function>fann_set_activation_steepness</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-get-bias-array" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_get_bias_array</refname>
<refpurpose>Get the number of bias in each layer in the network</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>array</type><methodname>fann_get_bias_array</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
</methodsynopsis>
<para>
Get the number of bias in each layer in the network.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
An array of numbers of bias in each layer
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-get-bit-fail-limit" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_get_bit_fail_limit</refname>
<refpurpose>Returns the bit fail limit used during training</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>float</type><methodname>fann_get_bit_fail_limit</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
</methodsynopsis>
<para>
Returns the bit fail limit used during training.
</para>
<para>
The bit fail limit is used during training where the <link linkend="constants.fann-stopfunc">stop function</link>
is set to <constant>FANN_STOPFUNC_BIT</constant>.
</para>
<para>
The limit is the maximum accepted difference between the desired output and the actual output during training.
Each output that diverges more than this limit is counted as an error bit. This difference is divided by two
when dealing with symmetric activation functions, so that symmetric and not symmetric activation functions
can use the same limit.
</para>
<para>
The default bit fail limit is 0.35.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
The bit fail limit, or &false; on error.
</para>
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_set_bit_fail_limit</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-get-bit-fail" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_get_bit_fail</refname>
<refpurpose>The number of fail bits</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>int</type><methodname>fann_get_bit_fail</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
</methodsynopsis>
<para>
The number of fail bits; means the number of output neurons which differ more than the bit fail limit
(see <function>fann_get_bit_fail_limit</function>, <function>fann_set_bit_fail_limit</function>).
The bits are counted in all of the training data, so this number can be higher than the number of training data.
</para>
<para>
This value is reset by <function>fann_reset_MSE</function> and updated by all the same functions
which also updates the MSE value (e.g. <function>fann_test_data</function>, <function>fann_train_epoch</function>)
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
The number of bits fail, or &false; on error.
</para>
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_get_MSE</function></member>
<member><function>fann_reset_MSE</function></member>
<member><function>fann_test_data</function></member>
<member><function>fann_train_epoch</function></member>
<member><function>fann_get_bit_fail_limit</function></member>
<member><function>fann_set_bit_fail_limit</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-get-cascade-activation-functions-count" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_get_cascade_activation_functions_count</refname>
<refpurpose>Returns the number of cascade activation functions</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>int</type><methodname>fann_get_cascade_activation_functions_count</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
</methodsynopsis>
<para>
The number of activation functions in the <function>fann_get_cascade_activation_functions</function> array.
</para>
<para>
The default number of activation functions is 6.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
The number of cascade activation functions, or &false; on error.
</para>
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_get_cascade_activation_functions</function></member>
<member><function>fann_set_cascade_activation_functions</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-get-cascade-activation-functions" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_get_cascade_activation_functions</refname>
<refpurpose>Returns the cascade activation functions</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>array</type><methodname>fann_get_cascade_activation_functions</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
</methodsynopsis>
<para>
The cascade activation functions array is an array of the different activation functions used by the candidates
</para>
<para>
See <function>fann_get_cascade_num_candidates</function> for a description of which candidate neurons will be generated by this array.
</para>
<para>
The default activation functions are <constant>FANN_SIGMOID</constant>, <constant>FANN_SIGMOID_SYMMETRIC</constant>,
<constant>FANN_GAUSSIAN</constant>, <constant>FANN_GAUSSIAN_SYMMETRIC</constant>, <constant>FANN_ELLIOT</constant>,
<constant>FANN_ELLIOT_SYMMETRIC</constant>.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
The cascade activation functions, or &false; on error.
</para>
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_get_cascade_activation_functions_count</function></member>
<member><function>fann_set_cascade_activation_functions</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-get-cascade-activation-steepnesses-count" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_get_cascade_activation_steepnesses_count</refname>
<refpurpose>The number of activation steepnesses</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>int</type><methodname>fann_get_cascade_activation_steepnesses_count</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
</methodsynopsis>
<para>
The number of activation steepnesses in the <function>fann_get_cascade_activation_functions</function> array.
</para>
<para>
The default number of activation steepnesses is 4.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
The number of activation steepnesses, or &false; on error.
</para>
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_get_cascade_activation_steepnesses</function></member>
<member><function>fann_set_cascade_activation_functions</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-get-cascade-activation-steepnesses" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_get_cascade_activation_steepnesses</refname>
<refpurpose>Returns the cascade activation steepnesses</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>array</type><methodname>fann_get_cascade_activation_steepnesses</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
</methodsynopsis>
<para>
The cascade activation steepnesses array is an array of the different activation functions used by the candidates.
</para>
<para>
See <function>fann_get_cascade_num_candidates</function> for a description of which candidate neurons will be generated by this array.
</para>
<para>
The default activation steepnesses are {0.25, 0.50, 0.75, 1.00}.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
The cascade activation steepnesses, or &false; on error.
</para>
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_get_cascade_activation_steepnesses_count</function></member>
<member><function>fann_set_cascade_activation_steepnesses</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-get-cascade-candidate-change-fraction" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_get_cascade_candidate_change_fraction</refname>
<refpurpose>Returns the cascade candidate change fraction</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>float</type><methodname>fann_get_cascade_candidate_change_fraction</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
</methodsynopsis>
<para>
The cascade candidate change fraction is a number between 0 and 1 determining how large a fraction the <function>fann_get_MSE</function>
value should change within <function>fann_get_cascade_candidate_stagnation_epochs</function> during training of the candidate neurons,
in order for the training not to stagnate. If the training stagnates, the training of the candidate neurons will be ended
and the best candidate will be selected.
</para>
<para>
It means that if the MSE does not change by a fraction of <function>fann_get_cascade_candidate_change_fraction</function> during
a period of <function>fann_get_cascade_candidate_stagnation_epochs</function>, the training of the candidate neurons is stopped
because the training has stagnated.
</para>
<para>
If the cascade candidate change fraction is low, the candidate neurons will be trained more and if the fraction is high they will be trained less.
</para>
<para>
The default cascade candidate change fraction is 0.01, which is equalent to a 1% change in MSE.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
The cascade candidate change fraction, or &false; on error.
</para>
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_set_cascade_candidate_change_fraction</function></member>
<member><function>fann_get_MSE</function></member>
<member><function>fann_get_cascade_candidate_stagnation_epochs</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-get-cascade-candidate-limit" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_get_cascade_candidate_limit</refname>
<refpurpose>Return the candidate limit</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>float</type><methodname>fann_get_cascade_candidate_limit</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
</methodsynopsis>
<para>
The candidate limit is a limit for how much the candidate neuron may be trained. The limit is a limit
on the proportion between the MSE and candidate score.
</para>
<para>
Set this to a lower value to avoid overfitting and to a higher if overfitting is not a problem.
</para>
<para>
The default candidate limit is 1000.0.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
The candidate limit, or &false; on error.
</para>
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_set_cascade_candidate_limit</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-get-cascade-candidate-stagnation-epochs" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_get_cascade_candidate_stagnation_epochs</refname>
<refpurpose>Returns the number of cascade candidate stagnation epochs</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>float</type><methodname>fann_get_cascade_candidate_stagnation_epochs</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
</methodsynopsis>
<para>
The number of cascade candidate stagnation epochs determines the number of epochs training is allowed to continue
without changing the MSE by a fraction of <function>fann_get_cascade_candidate_change_fraction</function>.
</para>
<para>
See more info about this parameter in <function>fann_get_cascade_candidate_change_fraction</function>.
</para>
<para>
The default number of cascade candidate stagnation epochs is 12.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
The number of cascade candidate stagnation epochs, or &false; on error.
</para>
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_set_cascade_candidate_stagnation_epochs</function></member>
<member><function>fann_get_cascade_candidate_change_fraction</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-get-cascade-max-cand-epochs" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_get_cascade_max_cand_epochs</refname>
<refpurpose>Returns the maximum candidate epochs</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>int</type><methodname>fann_get_cascade_max_cand_epochs</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
</methodsynopsis>
<para>
The maximum candidate epochs determines the maximum number of epochs the input connections
to the candidates may be trained before adding a new candidate neuron.
</para>
<para>
The default max candidate epochs is 150.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
The maximum candidate epochs, or &false; on error.
</para>
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_set_cascade_max_cand_epochs</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-get-cascade-max-out-epochs" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_get_cascade_max_out_epochs</refname>
<refpurpose>Returns the maximum out epochs</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>int</type><methodname>fann_get_cascade_max_out_epochs</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
</methodsynopsis>
<para>
The maximum out epochs determines the maximum number of epochs the output connections may be
trained after adding a new candidate neuron.
</para>
<para>
The default max out epochs is 150.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
The maximum out epochs, or &false; on error.
</para>
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_set_cascade_max_out_epochs</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-get-cascade-min-cand-epochs" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_get_cascade_min_cand_epochs</refname>
<refpurpose>Returns the minimum candidate epochs</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>int</type><methodname>fann_get_cascade_min_cand_epochs</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
</methodsynopsis>
<para>
The minimum candidate epochs determines the minimum number of epochs the input connections
to the candidates may be trained before adding a new candidate neuron.
</para>
<para>
The default min candidate epochs is 50.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
The minimum candidate epochs, or &false; on error.
</para>
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_set_cascade_min_cand_epochs</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-get-cascade-min-out-epochs" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_get_cascade_min_out_epochs</refname>
<refpurpose>Returns the minimum out epochs</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>int</type><methodname>fann_get_cascade_min_out_epochs</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
</methodsynopsis>
<para>
The minimum out epochs determines the minimum number of epochs the output connections must be trained
after adding a new candidate neuron.
</para>
<para>
The default min out epochs is 50.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
The minimum out epochs, or &false; on error.
</para>
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_set_cascade_min_out_epochs</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-get-cascade-num-candidate-groups" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_get_cascade_num_candidate_groups</refname>
<refpurpose>Returns the number of candidate groups</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>int</type><methodname>fann_get_cascade_num_candidate_groups</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
</methodsynopsis>
<para>
The number of candidate groups is the number of groups of identical candidates which will be used during training.
</para>
<para>
This number can be used to have more candidates without having to define new parameters for the candidates.
</para>
<para>
See <function>fann_get_cascade_num_candidates</function> for a description of
which candidate neurons will be generated by this parameter.
</para>
<para>
The default number of candidate groups is 2.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
The number of candidate groups, or &false; on error.
</para>
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_set_cascade_num_candidate_groups</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-get-cascade-num-candidates" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_get_cascade_num_candidates</refname>
<refpurpose>Returns the number of candidates used during training</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>int</type><methodname>fann_get_cascade_num_candidates</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
</methodsynopsis>
<para>
The number of candidates used during training (calculated by multiplying
<function>fann_get_cascade_activation_functions_count</function>,
<function>fann_get_cascade_activation_steepnesses_count</function> and
<function>fann_get_cascade_num_candidate_groups</function>).
</para>
<para>
The actual candidates is defined by the <function>fann_get_cascade_activation_functions</function> and
<function>fann_get_cascade_activation_steepnesses</function> arrays. These arrays define the activation functions and
activation steepnesses used for the candidate neurons. If there are 2 activation functions in the activation function array and
3 steepnesses in the steepness array, then there will be 2x3=6 different candidates which will be trained. These 6 different
candidates can be copied into several candidate groups, where the only difference between these groups is the initial weights.
If the number of groups is set to 2, then the number of candidate neurons will be 2x3x2=12.
The number of candidate groups is defined by <function>fann_set_cascade_num_candidate_groups</function>.
</para>
<para>
The default number of candidates is 6x4x2 = 48
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
The number of candidates used during training, or &false; on error.
</para>
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_get_cascade_activation_functions</function></member>
<member><function>fann_get_cascade_activation_functions_count</function></member>
<member><function>fann_get_cascade_activation_steepnesses</function></member>
<member><function>fann_get_cascade_activation_steepnesses_count</function></member>
<member><function>fann_get_cascade_num_candidate_groups</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-get-cascade-output-change-fraction" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_get_cascade_output_change_fraction</refname>
<refpurpose>Returns the cascade output change fraction</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>float</type><methodname>fann_get_cascade_output_change_fraction</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
</methodsynopsis>
<para>
The cascade output change fraction is a number between 0 and 1 determining how large a fraction of the <function>fann_get_MSE</function>
value should change within <function>fann_get_cascade_output_stagnation_epochs</function> during training of the output connections,
in order for the training not to stagnate. If the training stagnates, the training of the output connections
will be ended and new candidates will be prepared.
</para>
<para>
It means that if the MSE does not change by a fraction of <function>fann_get_cascade_output_change_fraction</function> during
a period of <function>fann_get_cascade_output_stagnation_epochs</function>, the training of the output connections is
stopped because the training has stagnated.
</para>
<para>
If the cascade output change fraction is low, the output connections will be trained more and if the fraction is high,
they will be trained less.
</para>
<para>
The default cascade output change fraction is 0.01, which is equalent to a 1% change in MSE.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
The cascade output change fraction, or &false; on error.
</para>
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_set_cascade_output_change_fraction</function></member>
<member><function>fann_get_MSE</function></member>
<member><function>fann_get_cascade_output_stagnation_epochs</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-get-cascade-output-stagnation-epochs" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_get_cascade_output_stagnation_epochs</refname>
<refpurpose>Returns the number of cascade output stagnation epochs</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>int</type><methodname>fann_get_cascade_output_stagnation_epochs</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
</methodsynopsis>
<para>
The number of cascade output stagnation epochs determines the number of epochs training is allowed to continue
without changing the MSE by a fraction of <function>fann_get_cascade_output_change_fraction</function>.
</para>
<para>
See more info about this parameter in <function>fann_get_cascade_output_change_fraction</function>.
</para>
<para>
The default number of cascade output stagnation epochs is 12.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
The number of cascade output stagnation epochs, or &false; on error.
</para>
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_set_cascade_output_stagnation_epochs</function></member>
<member><function>fann_get_cascade_output_change_fraction</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-get-cascade-weight-multiplier" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_get_cascade_weight_multiplier</refname>
<refpurpose>Returns the weight multiplier</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>float</type><methodname>fann_get_cascade_weight_multiplier</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
</methodsynopsis>
<para>
The weight multiplier is a parameter which is used to multiply the weights from the candidate neuron before adding
the neuron to the neural network. This parameter is usually between 0 and 1, and is used to make the training a bit less aggressive.
</para>
<para>
The default weight multiplier is 0.4.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
The weight multiplier, or &false; on error.
</para>
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_set_cascade_weight_multiplier</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-get-connection-array" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_get_connection_array</refname>
<refpurpose>Get connections in the network</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>array</type><methodname>fann_get_connection_array</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
</methodsynopsis>
<para>
Get connections in the network.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
An array of connections in the network
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-get-connection-rate" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_get_connection_rate</refname>
<refpurpose>Get the connection rate used when the network was created</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>float</type><methodname>fann_get_connection_rate</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
</methodsynopsis>
<para>
Get the connection rate used when the network was created.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
The connection rate used when the network was created, or &false; on error.
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-get-errno" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_get_errno</refname>
<refpurpose>Returns the last error number</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>int</type><methodname>fann_get_errno</methodname>
<methodparam><type>resource</type><parameter>errdat</parameter></methodparam>
</methodsynopsis>
<para>
Returns the last error number.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>errdat</parameter></term>
<listitem>
&fann.errdat.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
The error number, or &false; on error.
</para>
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_reset_errno</function></member>
<member><function>fann_get_errstr</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-get-errstr" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_get_errstr</refname>
<refpurpose>Returns the last errstr</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>string</type><methodname>fann_get_errstr</methodname>
<methodparam><type>resource</type><parameter>errdat</parameter></methodparam>
</methodsynopsis>
<para>
Returns the last errstr.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>errdat</parameter></term>
<listitem>
&fann.errdat.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
The last error string, or &false; on error.
</para>
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_reset_errstr</function></member>
<member><function>fann_get_errno</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-get-layer-array" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_get_layer_array</refname>
<refpurpose>Get the number of neurons in each layer in the network</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>array</type><methodname>fann_get_layer_array</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
</methodsynopsis>
<para>
Get the number of neurons in each layer in the neural network.
</para>
<para>
Bias is not included so the layers match the fann_create functions.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
An array of numbers of neurons in each leayer
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-get-learning-momentum" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_get_learning_momentum</refname>
<refpurpose>Returns the learning momentum</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>float</type><methodname>fann_get_learning_momentum</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
</methodsynopsis>
<para>
The learning momentum can be used to speed up <constant>FANN_TRAIN_INCREMENTAL</constant> training.
A too high momentum will however not benefit training. Setting momentum to 0 will be the same as
not using the momentum parameter. The recommended value of this parameter is between 0.0 and 1.0.
</para>
<para>
The default momentum is 0.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
&fann.return.bool;
<para>
The learning momentum, or &false; on error.
</para>
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_set_learning_momentum</function></member>
<member><function>fann_set_training_algorithm</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-get-learning-rate" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_get_learning_rate</refname>
<refpurpose>Returns the learning rate</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>float</type><methodname>fann_get_learning_rate</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
</methodsynopsis>
<para>
The learning rate is used to determine how aggressive training should be for some of the training algorithms
(<constant>FANN_TRAIN_INCREMENTAL</constant>, <constant>FANN_TRAIN_BATCH</constant>, <constant>FANN_TRAIN_QUICKPROP</constant>).
Do however note that it is not used in <constant>FANN_TRAIN_RPROP</constant>.
</para>
<para>
The default learning rate is 0.7.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
The learning rate, or &false; on error.
</para>
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_set_learning_rate</function></member>
<member><function>fann_set_training_algorithm</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-get-mse" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_get_MSE</refname>
<refpurpose>Reads the mean square error from the network</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>float</type><methodname>fann_get_MSE</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
</methodsynopsis>
<para>
Reads the mean square error from the network.
</para>
<para>
Reads the mean square error from the network. This value is calculated during training or testing and can therefore
sometimes be a bit off if the weights have been changed since the last calculation of the value.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
The mean square error, or &false; on error.
</para>
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_test_data</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-get-network-type" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_get_network_type</refname>
<refpurpose>Get the type of neural network it was created as</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>int</type><methodname>fann_get_network_type</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
</methodsynopsis>
<para>
Get the type of neural network it was created as.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
<link linkend="constants.fann-nettype">Network type</link> constant, or &false; on error.
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-get-num-input" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_get_num_input</refname>
<refpurpose>Get the number of input neurons</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>int</type><methodname>fann_get_num_input</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
</methodsynopsis>
<para>
Get the number of input neurons.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
Number of input neurons, or &false; on error
</para>
</refsect1>
</refentry>
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reference/fann/functions/fann-get-num-layers.xml Normal file
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-get-num-layers" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_get_num_layers</refname>
<refpurpose>Get the number of layers in the neural network</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>int</type><methodname>fann_get_num_layers</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
</methodsynopsis>
<para>
Get the number of layers in the neural network.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
The number of leayers in the neural network, or &false; on error.
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-get-num-output" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_get_num_output</refname>
<refpurpose>Get the number of output neurons</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>int</type><methodname>fann_get_num_output</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
</methodsynopsis>
<para>
Get the number of output neurons.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
Number of output neurons, or &false; on error
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-get-quickprop-decay" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_get_quickprop_decay</refname>
<refpurpose>Returns the decay which is a factor that weights should decrease in each iteration during quickprop training</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>float</type><methodname>fann_get_quickprop_decay</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
</methodsynopsis>
<para>
The decay is a small negative valued number which is a factor that the weights should decrease in each iteration
during quickprop training. This is used to make sure that the weights do not become too high during training.
</para>
<para>
The default decay is -0.0001.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
The decay, or &false; on error.
</para>
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_set_quickprop_decay</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-get-quickprop-mu" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_get_quickprop_mu</refname>
<refpurpose>Returns the mu factor</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>float</type><methodname>fann_get_quickprop_mu</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
</methodsynopsis>
<para>
The mu factor is used to increase and decrease the step-size during quickprop training. The mu factor should always be above 1,
since it would otherwise decrease the step-size when it was suppose to increase it.
</para>
<para>
The default mu factor is 1.75.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
The mu factor, or &false; on error.
</para>
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_set_quickprop_mu</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-get-rprop-decrease-factor" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_get_rprop_decrease_factor</refname>
<refpurpose>Returns the increase factor used during RPROP training</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>float</type><methodname>fann_get_rprop_decrease_factor</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
</methodsynopsis>
<para>
The decrease factor is a value smaller than 1, which is used to decrease the step-size during RPROP training.
</para>
<para>
The default decrease factor is 0.5.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
The decrease factor, or &false; on error.
</para>
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_set_rprop_decrease_factor</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-get-rprop-delta-max" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_get_rprop_delta_max</refname>
<refpurpose>Returns the maximum step-size</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>float</type><methodname>fann_get_rprop_delta_max</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
</methodsynopsis>
<para>
The maximum step-size is a positive number determining how large the maximum step-size may be.
</para>
<para>
The default delta max is 50.0.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
The maximum step-size, or &false; on error.
</para>
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_set_rprop_delta_max</function></member>
<member><function>fann_get_rprop_delta_min</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-get-rprop-delta-min" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_get_rprop_delta_min</refname>
<refpurpose>Returns the minimum step-size</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>float</type><methodname>fann_get_rprop_delta_min</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
</methodsynopsis>
<para>
The minimum step-size is a small positive number determining how small the minimum step-size may be.
</para>
<para>
The default value delta min is 0.0.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
The minimum step-size, or &false; on error.
</para>
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_set_rprop_delta_min</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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reference/fann/functions/fann-get-rprop-delta-zero.xml Normal file
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-get-rprop-delta-zero" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_get_rprop_delta_zero</refname>
<refpurpose>Returns the initial step-size</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>ReturnType</type><methodname>fann_get_rprop_delta_zero</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
</methodsynopsis>
<para>
The initial step-size is a positive number determining the initial step size.
</para>
<para>
The default delta zero is 0.1.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
The initial step-size, or &false; on error.
</para>
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_set_rprop_delta_zero</function></member>
<member><function>fann_get_rprop_delta_min</function></member>
<member><function>fann_get_rprop_delta_max</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-get-rprop-increase-factor" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_get_rprop_increase_factor</refname>
<refpurpose>Returns the increase factor used during RPROP training</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>float</type><methodname>fann_get_rprop_increase_factor</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
</methodsynopsis>
<para>
The increase factor is a value larger than 1, which is used to increase the step-size during RPROP training.
</para>
<para>
The default increase factor is 1.2.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
The increase factor, or &false; on error.
</para>
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_set_rprop_increase_factor</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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reference/fann/functions/fann-get-sarprop-step-error-shift.xml Normal file
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-get-sarprop-step-error-shift" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_get_sarprop_step_error_shift</refname>
<refpurpose>Returns the sarprop step error shift</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>float</type><methodname>fann_get_sarprop_step_error_shift</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
</methodsynopsis>
<para>
Returns the sarprop step error shift.
</para>
<para>
The default step error shift is 1.385.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
The sarprop step error shift , or &false; on error.
</para>
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_set_sarprop_step_error_shift</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-get-sarprop-step-error-threshold-factor" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_get_sarprop_step_error_threshold_factor</refname>
<refpurpose>Returns the sarprop step error threshold factor</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>float</type><methodname>fann_get_sarprop_step_error_threshold_factor</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
</methodsynopsis>
<para>
The sarprop step error threshold factor.
</para>
<para>
The default factor is 0.1.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
The sarprop step error threshold factor, or &false; on error.
</para>
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_set_sarprop_step_error_threshold_factor</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-get-sarprop-temperature" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_get_sarprop_temperature</refname>
<refpurpose>Returns the sarprop temperature</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>float</type><methodname>fann_get_sarprop_temperature</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
</methodsynopsis>
<para>
Returns the sarprop temperature.
</para>
<para>
The default temperature is 0.015.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
The sarprop temperature, or &false; on error.
</para>
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_set_sarprop_temperature</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-get-sarprop-weight-decay-shift" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_get_sarprop_weight_decay_shift</refname>
<refpurpose>Returns the sarprop weight decay shift</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>float</type><methodname>fann_get_sarprop_weight_decay_shift</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
</methodsynopsis>
<para>
The sarprop weight decay shift.
</para>
<para>
The default delta max is -6.644.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
The sarprop weight decay shift, or &false; on error.
</para>
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_set_sarprop_weight_decay_shift</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-get-total-connections" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_get_total_connections</refname>
<refpurpose>Get the total number of connections in the entire network</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>int</type><methodname>fann_get_total_connections</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
</methodsynopsis>
<para>
Get the total number of connections in the entire network.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
Total number of connections in the entire network, or &false; on error
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-get-total-neurons" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_get_total_neurons</refname>
<refpurpose>Get the total number of neurons in the entire network</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>int</type><methodname>fann_get_total_neurons</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
</methodsynopsis>
<para>
Get the total number of neurons in the entire network. This number does also include the bias neurons,
so a 2-4-2 network has 2+4+2 +2(bias) = 10 neurons.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
Total number of neurons in the entire network, or &false; on error.
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-get-train-error-function" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_get_train_error_function</refname>
<refpurpose>Returns the error function used during training</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>int</type><methodname>fann_get_train_error_function</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
</methodsynopsis>
<para>
Returns the error function used during training.
</para>
<para>
The error functions are described further in <link linkend="constants.fann-errorfunc">error functions</link> constants.
</para>
<para>
The default error function is <constant>FANN_ERRORFUNC_TANH</constant>.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
The <link linkend="constants.fann-errorfunc">error function</link> constant, or &false; on error.
</para>
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_set_train_error_function</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-get-train-stop-function" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_get_train_stop_function</refname>
<refpurpose>Returns the the stop function used during training</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>int</type><methodname>fann_get_train_stop_function</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
</methodsynopsis>
<para>
Returns the the stop function used during training.
</para>
<para>
The stop functions are described further in <link linkend="constants.fann-stopfunc">stop functions</link> constants.
</para>
<para>
The default stop function is <constant>FANN_STOPFUNC_MSE</constant>.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
The <link linkend="constants.fann-stopfunc">stop function</link> constant, or &false; on error.
</para>
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_set_train_stop_function</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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reference/fann/functions/fann-get-training-algorithm.xml Normal file
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-get-training-algorithm" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_get_training_algorithm</refname>
<refpurpose>Returns the training algorithm</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>int</type><methodname>fann_get_training_algorithm</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
</methodsynopsis>
<para>
Returns the training algorithm. This training algorithm is used by <function>fann_train_on_data</function> and associated functions.
</para>
<para>
Note that this algorithm is also used during <function>fann_cascadetrain_on_data</function>, although only
<constant>FANN_TRAIN_RPROP</constant> and <constant>FANN_TRAIN_QUICKPROP</constant> is allowed during cascade training.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
<link linkend="constants.fann-train">Training algorithm</link> constant, or &false; on error.
</para>
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_set_training_algorithm</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-init-weights" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_init_weights</refname>
<refpurpose>Initialize the weights using Widrow + Nguyen’s algorithm</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>bool</type><methodname>fann_init_weights</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
<methodparam><type>resource</type><parameter>train_data</parameter></methodparam>
</methodsynopsis>
<para>
Initialize the weights using Widrow + Nguyen’s algorithm.
</para>
<para>
This function behaves similarly to <function>fann_randomize_weights</function>. It will use the algorithm developed by
Derrick Nguyen and Bernard Widrow to set the weights in such a way as to speed up training. This technique is not always
successful, and in some cases can be less efficient than a purely random initialization.
</para>
<para>
The algorithm requires access to the range of the input data (for example largest and smallest input), and therefore
accepts a second argument, data, which is the training data that will be used to train the network.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
<varlistentry>
<term><parameter>train_data</parameter></term>
<listitem>
&fann.train.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
&fann.return.bool;
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_randomize_weights</function></member>
<member><function>fann_read_train_from_file</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-length-train-data" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_length_train_data</refname>
<refpurpose>Returns the number of training patterns in the train data</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>int</type><methodname>fann_length_train_data</methodname>
<methodparam><type>resource</type><parameter>data</parameter></methodparam>
</methodsynopsis>
<para>
Returns the number of training patterns in the train data <type>resource</type>.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>data</parameter></term>
<listitem>
&fann.train.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
Number of elements in the train data <type>resource</type>, or &false; on error.
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-merge-train-data" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_merge_train_data</refname>
<refpurpose>Merges the train data</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>resource</type><methodname>fann_merge_train_data</methodname>
<methodparam><type>resource</type><parameter>data1</parameter></methodparam>
<methodparam><type>resource</type><parameter>data2</parameter></methodparam>
</methodsynopsis>
<para>
Merges the data from data1 and data2 into a new train data <type>resource</type>.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>data1</parameter></term>
<listitem>
&fann.train.description;
</listitem>
</varlistentry>
<varlistentry>
<term><parameter>data2</parameter></term>
<listitem>
&fann.train.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
New merged train data <type>resource</type>, or &false; on error.
</para>
</refsect1>
</refentry>
<!-- Keep this comment at the end of the file
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End:
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-num-input-train-data" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_num_input_train_data</refname>
<refpurpose>Returns the number of inputs in each of the training patterns in the train data</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>int</type><methodname>fann_num_input_train_data</methodname>
<methodparam><type>resource</type><parameter>data</parameter></methodparam>
</methodsynopsis>
<para>
Returns the number of inputs in each of the training patterns in the train data <type>resource</type>.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>data</parameter></term>
<listitem>
&fann.train.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
The number of inputs, or &false; on error.
</para>
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_length_train_data</function></member>
<member><function>fann_num_output_train_data</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
<!-- Keep this comment at the end of the file
Local variables:
mode: sgml
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sgml-minimize-attributes:nil
sgml-always-quote-attributes:t
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sgml-default-dtd-file:"~/.phpdoc/manual.ced"
sgml-exposed-tags:nil
sgml-local-catalogs:nil
sgml-local-ecat-files:nil
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-num-output-train-data" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_num_output_train_data</refname>
<refpurpose>Returns the number of outputs in each of the training patterns in the train data</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>int</type><methodname>fann_num_output_train_data</methodname>
<methodparam><type>resource</type><parameter>data</parameter></methodparam>
</methodsynopsis>
<para>
Returns the number of outputs in each of the training patterns in the train data <type>resource</type>.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>data</parameter></term>
<listitem>
&fann.train.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
The number of outputs, or &false; on error.
</para>
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_length_train_data</function></member>
<member><function>fann_num_input_train_data</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
<!-- Keep this comment at the end of the file
Local variables:
mode: sgml
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sgml-minimize-attributes:nil
sgml-always-quote-attributes:t
sgml-indent-step:1
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sgml-default-dtd-file:"~/.phpdoc/manual.ced"
sgml-exposed-tags:nil
sgml-local-catalogs:nil
sgml-local-ecat-files:nil
End:
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-print-error" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_print_error</refname>
<refpurpose>Prints the error string</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>void</type><methodname>fann_print_error</methodname>
<methodparam><type>string</type><parameter>errdat</parameter></methodparam>
</methodsynopsis>
<para>
Prints the error string.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>errdat</parameter></term>
<listitem>
&fann.errdat.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
&fann.return.void;
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_get_errstr</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
<!-- Keep this comment at the end of the file
Local variables:
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sgml-default-dtd-file:"~/.phpdoc/manual.ced"
sgml-exposed-tags:nil
sgml-local-catalogs:nil
sgml-local-ecat-files:nil
End:
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-randomize-weights" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_randomize_weights</refname>
<refpurpose>Give each connection a random weight between min_weight and max_weight</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>bool</type><methodname>fann_randomize_weights</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
<methodparam><type>float</type><parameter>min_weight</parameter></methodparam>
<methodparam><type>float</type><parameter>max_weight</parameter></methodparam>
</methodsynopsis>
<para>
Give each connection a random weight between <parameter>min_weight</parameter> and <parameter>max_weight</parameter>
</para>
<para>
From the beginning the weights are random between -0.1 and 0.1.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
<varlistentry>
<term><parameter>min_weight</parameter></term>
<listitem>
<para>
Minimum weight value
</para>
</listitem>
</varlistentry>
<varlistentry>
<term><parameter>max_weight</parameter></term>
<listitem>
<para>
Maximum weight value
</para>
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
&fann.return.bool;
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_init_weights</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
<!-- Keep this comment at the end of the file
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sgml-default-dtd-file:"~/.phpdoc/manual.ced"
sgml-exposed-tags:nil
sgml-local-catalogs:nil
sgml-local-ecat-files:nil
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-read-train-from-file" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_read_train_from_file</refname>
<refpurpose>Reads a file that stores training data</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>resource</type><methodname>fann_read_train_from_file</methodname>
<methodparam><type>string</type><parameter>filename</parameter></methodparam>
</methodsynopsis>
<para>
Reads a file that stores training data.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>filename</parameter></term>
<listitem>
<para>
The input file in the following format:
</para>
<programlisting role="txt">
<![CDATA[
num_train_data num_input num_output
inputdata seperated by space
outputdata seperated by space
.
.
.
inputdata seperated by space
outputdata seperated by space
]]>
</programlisting>
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
&fann.return.train;
</refsect1>
<refsect1 role="examples">
&reftitle.examples;
<para>
<example>
<title><methodname>fann_read_train_from_file</methodname> example</title>
<programlisting role="php">
<![CDATA[
<?php
$train_data = fann_read_train_from_file("xor.data");
if ($train_data) {
// Do something with $train_data for XOR function
}
?>
]]>
</programlisting>
<para>Contents of xor.data</para>
<programlisting role="txt">
<![CDATA[
4 2 1
-1 -1
-1
-1 1
1
1 -1
1
1 1
-1
]]>
</programlisting>
</example>
</para>
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_train_on_data</function></member>
<member><function>fann_destroy_train</function></member>
<member><function>fann_save_train</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
<!-- Keep this comment at the end of the file
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-reset-errno" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_reset_errno</refname>
<refpurpose>Resets the last error number</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>void</type><methodname>fann_reset_errno</methodname>
<methodparam><type>resource</type><parameter>errdat</parameter></methodparam>
</methodsynopsis>
<para>
Resets the last error number.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>errdat</parameter></term>
<listitem>
&fann.errdat.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
&fann.return.void;
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_get_errno</function></member>
<member><function>fann_reset_errstr</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
<!-- Keep this comment at the end of the file
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-reset-errstr" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_reset_errstr</refname>
<refpurpose>Resets the last error string</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>void</type><methodname>fann_reset_errstr</methodname>
<methodparam><type>resource</type><parameter>errdat</parameter></methodparam>
</methodsynopsis>
<para>
Resets the last error string.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>errdat</parameter></term>
<listitem>
&fann.errdat.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
&fann.return.void;
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_get_errstr</function></member>
<member><function>fann_reset_errno</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
<!-- Keep this comment at the end of the file
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-reset-mse" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_reset_MSE</refname>
<refpurpose>Resets the mean square error from the network</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>bool</type><methodname>fann_reset_MSE</methodname>
<methodparam><type>string</type><parameter>ann</parameter></methodparam>
</methodsynopsis>
<para>
Resets the mean square error from the network.
</para>
<para>
This function also resets the number of bits that fail.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
&fann.return.bool;
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_get_MSE</function></member>
<member><function>fann_get_bit_fail</function></member>
<member><function>fann_get_bit_fail_limit</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
<!-- Keep this comment at the end of the file
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-run" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_run</refname>
<refpurpose>Will run input through the neural network</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>array</type><methodname>fann_run</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
<methodparam><type>array</type><parameter>input</parameter></methodparam>
</methodsynopsis>
<para>
Will run input through the neural network, returning an array of outputs, the number of which being equal
to the number of neurons in the output layer.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
<varlistentry>
<term><parameter>input</parameter></term>
<listitem>
<para>
Array of input values
</para>
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
<para>
Array of output values, or &false; on error
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-save-train" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_save_train</refname>
<refpurpose>Save the training structure to a file</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>bool</type><methodname>fann_save_train</methodname>
<methodparam><type>resource</type><parameter>data</parameter></methodparam>
<methodparam><type>string</type><parameter>file_name</parameter></methodparam>
</methodsynopsis>
<para>
Save the training data to a file, with the format as specified in <function>fann_read_train_from_file</function>.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>data</parameter></term>
<listitem>
&fann.train.description;
</listitem>
</varlistentry>
<varlistentry>
<term><parameter>file_name</parameter></term>
<listitem>
<para>
The file name of the file where training data is saved to.
</para>
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
&fann.return.bool;
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_read_train_from_file</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-save" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_save</refname>
<refpurpose>Saves the entire network to a configuration file</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>bool</type><methodname>fann_save</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
<methodparam><type>string</type><parameter>configuration_file</parameter></methodparam>
</methodsynopsis>
<para>
Saves the entire network to a configuration file.
</para>
<para>
The configuration file contains all information about the neural network and enables
<function>fann_create_from_file</function> to create an exact copy of the neural network
and all of the parameters associated with the neural network.
</para>
<para>
These three parameters (<function>fann_set_callback</function>, <function>fann_set_error_log</function>,
<function>fann_set_user_data</function>) are NOT saved to the file because they cannot safely be ported
to a different location. Also temporary parameters generated during training like <function>fann_get_MSE</function>
is not saved.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
<varlistentry>
<term><parameter>configuration_file</parameter></term>
<listitem>
<para>
The configuration file path.
</para>
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
&fann.return.bool;
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_create_from_file</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-scale-input-train-data" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_scale_input_train_data</refname>
<refpurpose>Scales the inputs in the training data to the specified range</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>bool</type><methodname>fann_scale_input_train_data</methodname>
<methodparam><type>resource</type><parameter>train_data</parameter></methodparam>
<methodparam><type>float</type><parameter>new_min</parameter></methodparam>
<methodparam><type>float</type><parameter>new_max</parameter></methodparam>
</methodsynopsis>
<para>
Scales the inputs in the training data to the specified range.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>train_data</parameter></term>
<listitem>
&fann.train.description;
</listitem>
</varlistentry>
<varlistentry>
<term><parameter>new_min</parameter></term>
<listitem>
<para>
New minimum after scaling inputs in training data.
</para>
</listitem>
</varlistentry>
<varlistentry>
<term><parameter>new_max</parameter></term>
<listitem>
<para>
New maximum after scaling inputs in training data.
</para>
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
&fann.return.bool;
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_scale_output_train_data</function></member>
<member><function>fann_scale_train_data</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-scale-input" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_scale_input</refname>
<refpurpose>Scale data in input vector before feed it to ann based on previously calculated parameters</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>bool</type><methodname>fann_scale_input</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
<methodparam><type>array</type><parameter>input_vector</parameter></methodparam>
</methodsynopsis>
<para>
Scale data in input vector before feed it to ann based on previously calculated parameters.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
<varlistentry>
<term><parameter>input_vector</parameter></term>
<listitem>
<para>
Input vector that will be scaled
</para>
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
&fann.return.bool;
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_descale_input</function></member>
<member><function>fann_scale_output</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-scale-output-train-data" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_scale_output_train_data</refname>
<refpurpose>Scales the outputs in the training data to the specified range</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>bool</type><methodname>fann_scale_output_train_data</methodname>
<methodparam><type>resource</type><parameter>train_data</parameter></methodparam>
<methodparam><type>float</type><parameter>new_min</parameter></methodparam>
<methodparam><type>float</type><parameter>new_max</parameter></methodparam>
</methodsynopsis>
<para>
Scales the outputs in the training data to the specified range.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>train_data</parameter></term>
<listitem>
&fann.train.description;
</listitem>
</varlistentry>
<varlistentry>
<term><parameter>new_min</parameter></term>
<listitem>
<para>
New minimum after scaling outputs in training data.
</para>
</listitem>
</varlistentry>
<varlistentry>
<term><parameter>new_max</parameter></term>
<listitem>
<para>
New maximum after scaling outputs in training data.
</para>
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
&fann.return.bool;
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_scale_input_train_data</function></member>
<member><function>fann_scale_train_data</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-scale-output" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_scale_output</refname>
<refpurpose>Scale data in output vector before feed it to ann based on previously calculated parameters</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>bool</type><methodname>fann_scale_output</methodname>
<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
<methodparam><type>array</type><parameter>output_vector</parameter></methodparam>
</methodsynopsis>
<para>
Scale data in output vector before feed it to ann based on previously calculated parameters.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>ann</parameter></term>
<listitem>
&fann.ann.description;
</listitem>
</varlistentry>
<varlistentry>
<term><parameter>output_vector</parameter></term>
<listitem>
<para>
Output vector that will be scaled
</para>
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
&fann.return.bool;
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_descale_output</function></member>
<member><function>fann_scale_input</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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<?xml version="1.0" encoding="utf-8"?>
<!-- $Revision$ -->
<refentry xml:id="function.fann-scale-train-data" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
<refnamediv>
<refname>fann_scale_train_data</refname>
<refpurpose>Scales the inputs and outputs in the training data to the specified range</refpurpose>
</refnamediv>
<refsect1 role="description">
&reftitle.description;
<methodsynopsis>
<type>bool</type><methodname>fann_scale_train_data</methodname>
<methodparam><type>resource</type><parameter>train_data</parameter></methodparam>
<methodparam><type>float</type><parameter>new_min</parameter></methodparam>
<methodparam><type>float</type><parameter>new_max</parameter></methodparam>
</methodsynopsis>
<para>
Scales the inputs and outputs in the training data to the specified range.
</para>
</refsect1>
<refsect1 role="parameters">
&reftitle.parameters;
<variablelist>
<varlistentry>
<term><parameter>train_data</parameter></term>
<listitem>
&fann.train.description;
</listitem>
</varlistentry>
<varlistentry>
<term><parameter>new_min</parameter></term>
<listitem>
<para>
New minimum after scaling inputs and outputs in training data.
</para>
</listitem>
</varlistentry>
<varlistentry>
<term><parameter>new_max</parameter></term>
<listitem>
<para>
New maximum after scaling inputs and outputs in training data.
</para>
</listitem>
</varlistentry>
</variablelist>
</refsect1>
<refsect1 role="returnvalues">
&reftitle.returnvalues;
&fann.return.bool;
</refsect1>
<refsect1 role="seealso">
&reftitle.seealso;
<para>
<simplelist>
<member><function>fann_scale_output_train_data</function></member>
<member><function>fann_scale_input_train_data</function></member>
</simplelist>
</para>
</refsect1>
</refentry>
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