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<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.0 Frameset//EN""http://www.w3.org/TR/REC-html40/frameset.dtd"><!--NewPage--><HTML><HEAD><!-- Generated by javadoc on Wed Sep 04 10:31:50 CDT 2002 --><TITLE>: Class NeuralNetwork</TITLE><LINK REL ="stylesheet" TYPE="text/css" HREF="../../../stylesheet.css" TITLE="Style"></HEAD><BODY BGCOLOR="white"><!-- ========== START OF NAVBAR ========== --><A NAME="navbar_top"><!-- --></A><TABLE BORDER="0" WIDTH="100%" CELLPADDING="1" CELLSPACING="0"><TR><TD COLSPAN=2 BGCOLOR="#EEEEFF" CLASS="NavBarCell1"><A NAME="navbar_top_firstrow"><!-- --></A><TABLE BORDER="0" CELLPADDING="0" CELLSPACING="3"> <TR ALIGN="center" VALIGN="top"> <TD BGCOLOR="#EEEEFF" CLASS="NavBarCell1"> <A HREF="../../../overview-summary.html"><FONT CLASS="NavBarFont1"><B>Overview</B></FONT></A> </TD> <TD BGCOLOR="#EEEEFF" CLASS="NavBarCell1"> <A HREF="package-summary.html"><FONT CLASS="NavBarFont1"><B>Package</B></FONT></A> </TD> <TD BGCOLOR="#FFFFFF" CLASS="NavBarCell1Rev"> <FONT CLASS="NavBarFont1Rev"><B>Class</B></FONT> </TD> <TD BGCOLOR="#EEEEFF" CLASS="NavBarCell1"> <A HREF="package-tree.html"><FONT CLASS="NavBarFont1"><B>Tree</B></FONT></A> </TD> <TD BGCOLOR="#EEEEFF" CLASS="NavBarCell1"> <A HREF="../../../deprecated-list.html"><FONT CLASS="NavBarFont1"><B>Deprecated</B></FONT></A> </TD> <TD BGCOLOR="#EEEEFF" CLASS="NavBarCell1"> <A HREF="../../../index-all.html"><FONT CLASS="NavBarFont1"><B>Index</B></FONT></A> </TD> <TD BGCOLOR="#EEEEFF" CLASS="NavBarCell1"> <A HREF="../../../help-doc.html"><FONT CLASS="NavBarFont1"><B>Help</B></FONT></A> </TD> </TR></TABLE></TD><TD ALIGN="right" VALIGN="top" ROWSPAN=3><EM></EM></TD></TR><TR><TD BGCOLOR="white" CLASS="NavBarCell2"><FONT SIZE="-2"> <A HREF="../../../weka/classifiers/neural/NeuralConnection.html"><B>PREV CLASS</B></A> <A HREF="../../../weka/classifiers/neural/NeuralNetwork.NeuralEnd.html"><B>NEXT CLASS</B></A></FONT></TD><TD BGCOLOR="white" CLASS="NavBarCell2"><FONT SIZE="-2"> <A HREF="../../../index.html" TARGET="_top"><B>FRAMES</B></A> <A HREF="NeuralNetwork.html" TARGET="_top"><B>NO FRAMES</B></A></FONT></TD></TR><TR><TD VALIGN="top" CLASS="NavBarCell3"><FONT SIZE="-2"> SUMMARY: <A HREF="#inner_class_summary">INNER</A> | FIELD | <A HREF="#constructor_summary">CONSTR</A> | <A HREF="#method_summary">METHOD</A></FONT></TD><TD VALIGN="top" CLASS="NavBarCell3"><FONT SIZE="-2">DETAIL: FIELD | <A HREF="#constructor_detail">CONSTR</A> | <A HREF="#method_detail">METHOD</A></FONT></TD></TR></TABLE><!-- =========== END OF NAVBAR =========== --><HR><!-- ======== START OF CLASS DATA ======== --><H2><FONT SIZE="-1">weka.classifiers.neural</FONT><BR>Class NeuralNetwork</H2><PRE>java.lang.Object | +--<A HREF="../../../weka/classifiers/Classifier.html">weka.classifiers.Classifier</A> | +--<A HREF="../../../weka/classifiers/DistributionClassifier.html">weka.classifiers.DistributionClassifier</A> | +--<B>weka.classifiers.neural.NeuralNetwork</B></PRE><DL><DT><B>All Implemented Interfaces:</B> <DD>java.lang.Cloneable, <A HREF="../../../weka/core/OptionHandler.html">OptionHandler</A>, java.io.Serializable, <A HREF="../../../weka/core/WeightedInstancesHandler.html">WeightedInstancesHandler</A></DD></DL><HR><DL><DT>public class <B>NeuralNetwork</B><DT>extends <A HREF="../../../weka/classifiers/DistributionClassifier.html">DistributionClassifier</A><DT>implements <A HREF="../../../weka/core/OptionHandler.html">OptionHandler</A>, <A HREF="../../../weka/core/WeightedInstancesHandler.html">WeightedInstancesHandler</A></DL><P>A Classifier that uses backpropagation to classify instances. This network can be built by hand, created by an algorithm or both. The network can also be monitored and modified during training time. The nodes in this network are all sigmoid (except for when the class is numeric in which case the the output nodes become unthresholded linear units).<P><DL><DT><B>See Also: </B><DD><A HREF="../../../serialized-form.html#weka.classifiers.neural.NeuralNetwork">Serialized Form</A></DL><HR><P><!-- ======== INNER CLASS SUMMARY ======== --><A NAME="inner_class_summary"><!-- --></A><TABLE BORDER="1" CELLPADDING="3" CELLSPACING="0" WIDTH="100%"><TR BGCOLOR="#CCCCFF" CLASS="TableHeadingColor"><TD COLSPAN=2><FONT SIZE="+2"><B>Inner Class Summary</B></FONT></TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>protected class</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/neural/NeuralNetwork.NeuralEnd.html">NeuralNetwork.NeuralEnd</A></B></CODE><BR> This inner class is used to connect the nodes in the network up to the data that they are classifying, Note that objects of this class are only suitable to go on the attribute side or class side of the network and not both.</TD></TR></TABLE> <!-- =========== FIELD SUMMARY =========== --><!-- ======== CONSTRUCTOR SUMMARY ======== --><A NAME="constructor_summary"><!-- --></A><TABLE BORDER="1" CELLPADDING="3" CELLSPACING="0" WIDTH="100%"><TR BGCOLOR="#CCCCFF" CLASS="TableHeadingColor"><TD COLSPAN=2><FONT SIZE="+2"><B>Constructor Summary</B></FONT></TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><CODE><B><A HREF="../../../weka/classifiers/neural/NeuralNetwork.html#NeuralNetwork()">NeuralNetwork</A></B>()</CODE><BR> The constructor.</TD></TR></TABLE> <!-- ========== METHOD SUMMARY =========== --><A NAME="method_summary"><!-- --></A><TABLE BORDER="1" CELLPADDING="3" CELLSPACING="0" WIDTH="100%"><TR BGCOLOR="#CCCCFF" CLASS="TableHeadingColor"><TD COLSPAN=2><FONT SIZE="+2"><B>Method Summary</B></FONT></TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> java.lang.String</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/neural/NeuralNetwork.html#autoBuildTipText()">autoBuildTipText</A></B>()</CODE><BR> </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> void</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/neural/NeuralNetwork.html#blocker(boolean)">blocker</A></B>(boolean tf)</CODE><BR> A function used to stop the code that called buildclassifier from continuing on before the user has finished the decision tree.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> void</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/neural/NeuralNetwork.html#buildClassifier(weka.core.Instances)">buildClassifier</A></B>(<A HREF="../../../weka/core/Instances.html">Instances</A> i)</CODE><BR> Call this function to build and train a neural network for the training data provided.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> java.lang.String</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/neural/NeuralNetwork.html#decayTipText()">decayTipText</A></B>()</CODE><BR> </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> double[]</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/neural/NeuralNetwork.html#distributionForInstance(weka.core.Instance)">distributionForInstance</A></B>(<A HREF="../../../weka/core/Instance.html">Instance</A> i)</CODE><BR> Call this function to predict the class of an instance once a classification model has been built with the buildClassifier call.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> boolean</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/neural/NeuralNetwork.html#getAutoBuild()">getAutoBuild</A></B>()</CODE><BR> </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> boolean</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/neural/NeuralNetwork.html#getDecay()">getDecay</A></B>()</CODE><BR> </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> boolean</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/neural/NeuralNetwork.html#getGUI()">getGUI</A></B>()</CODE><BR> </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> java.lang.String</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/neural/NeuralNetwork.html#getHiddenLayers()">getHiddenLayers</A></B>()</CODE><BR> </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> double</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/neural/NeuralNetwork.html#getLearningRate()">getLearningRate</A></B>()</CODE><BR> </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> double</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/neural/NeuralNetwork.html#getMomentum()">getMomentum</A></B>()</CODE><BR> </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> boolean</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/neural/NeuralNetwork.html#getNominalToBinaryFilter()">getNominalToBinaryFilter</A></B>()</CODE><BR> </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> boolean</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/neural/NeuralNetwork.html#getNormalizeAttributes()">getNormalizeAttributes</A></B>()</CODE><BR> </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> boolean</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/neural/NeuralNetwork.html#getNormalizeNumericClass()">getNormalizeNumericClass</A></B>()</CODE><BR> </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> java.lang.String[]</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/neural/NeuralNetwork.html#getOptions()">getOptions</A></B>()</CODE><BR> Gets the current settings of NeuralNet.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> long</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/neural/NeuralNetwork.html#getRandomSeed()">getRandomSeed</A></B>()</CODE><BR> </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> boolean</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/neural/NeuralNetwork.html#getReset()">getReset</A></B>()</CODE><BR> </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> int</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/neural/NeuralNetwork.html#getTrainingTime()">getTrainingTime</A></B>()</CODE><BR> </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> int</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/neural/NeuralNetwork.html#getValidationSetSize()">getValidationSetSize</A></B>()</CODE><BR> </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> int</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/neural/NeuralNetwork.html#getValidationThreshold()">getValidationThreshold</A></B>()</CODE><BR> </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> java.lang.String</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/neural/NeuralNetwork.html#globalInfo()">globalInfo</A></B>()</CODE><BR> This will return a string describing the classifier.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> java.lang.String</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/neural/NeuralNetwork.html#GUITipText()">GUITipText</A></B>()</CODE><BR> </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> java.lang.String</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/neural/NeuralNetwork.html#hiddenLayersTipText()">hiddenLayersTipText</A></B>()</CODE><BR> </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> java.lang.String</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/neural/NeuralNetwork.html#learningRateTipText()">learningRateTipText</A></B>()</CODE><BR> </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> java.util.Enumeration</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/neural/NeuralNetwork.html#listOptions()">listOptions</A></B>()</CODE><BR> Returns an enumeration describing the available options</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>static void</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/neural/NeuralNetwork.html#main(java.lang.String[])">main</A></B>(java.lang.String[] argv)</CODE><BR> Main method for testing this class.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> java.lang.String</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/neural/NeuralNetwork.html#momentumTipText()">momentumTipText</A></B>()</CODE><BR> </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> java.lang.String</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/neural/NeuralNetwork.html#nominalToBinaryFilterTipText()">nominalToBinaryFilterTipText</A></B>()</CODE><BR> </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> java.lang.String</CODE></FONT></TD>⌨️ 快捷键说明
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