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https://github.com/sigmasternchen/php-doc-en
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git-svn-id: https://svn.php.net/repository/phpdoc/en/trunk@331220 c90b9560-bf6c-de11-be94-00142212c4b1
114 lines
3.8 KiB
XML
114 lines
3.8 KiB
XML
<?xml version="1.0" encoding="utf-8"?>
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<!-- $Revision$ -->
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<refentry xml:id="function.fann-cascadetrain-on-data" xmlns="http://docbook.org/ns/docbook" xmlns:xlink="http://www.w3.org/1999/xlink">
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<refnamediv>
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<refname>fann_cascadetrain_on_data</refname>
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<refpurpose>Trains on an entire dataset, for a period of time using the Cascade2 training algorithm</refpurpose>
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</refnamediv>
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<refsect1 role="description">
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&reftitle.description;
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<methodsynopsis>
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<type>bool</type><methodname>fann_cascadetrain_on_data</methodname>
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<methodparam><type>resource</type><parameter>ann</parameter></methodparam>
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<methodparam><type>resource</type><parameter>data</parameter></methodparam>
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<methodparam><type>int</type><parameter>max_neurons</parameter></methodparam>
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<methodparam><type>int</type><parameter>neurons_between_reports</parameter></methodparam>
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<methodparam><type>float</type><parameter>desired_error</parameter></methodparam>
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</methodsynopsis>
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<para>
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The cascade output change fraction is a number between 0 and 1 determining how large a fraction
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the <function>fann_get_MSE</function> value should change within <function>fann_get_cascade_output_stagnation_epochs</function>
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during training of the output connections, in order for the training not to stagnate. If the training stagnates,
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the training of the output connections will be ended and new candidates will be prepared.
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</para>
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<para>
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This training uses the parameters set using the fann_set_cascade_..., but it also uses another training algorithm
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as it’s internal training algorithm. This algorithm can be set to either <constant>FANN_TRAIN_RPROP</constant> or
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<constant>FANN_TRAIN_QUICKPROP</constant> by <function>fann_set_training_algorithm</function>, and the parameters
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set for these training algorithms will also affect the cascade training.
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</para>
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</refsect1>
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<refsect1 role="parameters">
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&reftitle.parameters;
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<variablelist>
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<varlistentry>
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<term><parameter>ann</parameter></term>
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<listitem>
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&fann.ann.description;
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</listitem>
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</varlistentry>
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<varlistentry>
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<term><parameter>data</parameter></term>
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<listitem>
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&fann.train.description;
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</listitem>
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</varlistentry>
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<varlistentry>
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<term><parameter>max_neurons</parameter></term>
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<listitem>
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<para>
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The maximum number of neurons to be added to neural network.
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</para>
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</listitem>
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</varlistentry>
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<varlistentry>
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<term><parameter>neurons_between_reports</parameter></term>
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<listitem>
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<para>
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The number of neurons between printing a status report. A value of zero means no reports should be printed.
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</para>
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</listitem>
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</varlistentry>
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<varlistentry>
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<term><parameter>desired_error</parameter></term>
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<listitem>
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<para>
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The desired <function>fann_get_MSE</function> or <function>fann_get_bit_fail</function>,
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depending on which stop function is chosen by <function>fann_set_train_stop_function</function>
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</para>
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</listitem>
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</varlistentry>
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</variablelist>
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</refsect1>
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<refsect1 role="returnvalues">
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&reftitle.returnvalues;
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&fann.return.bool;
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</refsect1>
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<refsect1 role="seealso">
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&reftitle.seealso;
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<para>
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<simplelist>
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<member><function>fann_train_on_data</function></member>
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<member><function>fann_cascadetrain_on_file</function></member>
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</simplelist>
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</para>
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</refsect1>
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</refentry>
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<!-- Keep this comment at the end of the file
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Local variables:
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mode: sgml
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sgml-omittag:t
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sgml-shorttag:t
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sgml-minimize-attributes:nil
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sgml-always-quote-attributes:t
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sgml-indent-step:1
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sgml-indent-data:t
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indent-tabs-mode:nil
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sgml-parent-document:nil
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sgml-default-dtd-file:"~/.phpdoc/manual.ced"
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sgml-exposed-tags:nil
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sgml-local-catalogs:nil
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sgml-local-ecat-files:nil
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End:
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vim600: syn=xml fen fdm=syntax fdl=2 si
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vim: et tw=78 syn=sgml
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vi: ts=1 sw=1
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-->
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