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<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/bayes/BayesNet.html#graphType()">graphType</A></B>()</CODE><BR> Returns the type of graph this classifier represents.</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/bayes/BayesNet.html#initCPTs()">initCPTs</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/bayes/BayesNet.html#initStructure()">initStructure</A></B>()</CODE><BR> Init structure initializes the structure to an empty graph or a Naive Bayes graph (depending on the -N flag).</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/bayes/BayesNet.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/bayes/BayesNet.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> double</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/bayes/BayesNet.html#measureAICScore()">measureAICScore</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/bayes/BayesNet.html#measureBayesScore()">measureBayesScore</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/bayes/BayesNet.html#measureBDeuScore()">measureBDeuScore</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/bayes/BayesNet.html#measureDivergence()">measureDivergence</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/bayes/BayesNet.html#measureEntropyScore()">measureEntropyScore</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/bayes/BayesNet.html#measureExtraArcs()">measureExtraArcs</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/bayes/BayesNet.html#measureMDLScore()">measureMDLScore</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/bayes/BayesNet.html#measureMissingArcs()">measureMissingArcs</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/bayes/BayesNet.html#measureReversedArcs()">measureReversedArcs</A></B>()</CODE><BR> </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>static java.lang.String[]</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/bayes/BayesNet.html#partitionOptions(java.lang.String[])">partitionOptions</A></B>(java.lang.String[] options)</CODE><BR> Returns the secondary set of options (if any) contained in the supplied options array.</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/bayes/BayesNet.html#searchAlgorithmTipText()">searchAlgorithmTipText</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/bayes/BayesNet.html#setBIFFile(java.lang.String)">setBIFFile</A></B>(java.lang.String sBIFFile)</CODE><BR> Set name of network in BIF file to compare with</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/bayes/BayesNet.html#setEstimator(weka.classifiers.bayes.net.estimate.BayesNetEstimator)">setEstimator</A></B>(<A HREF="../../../weka/classifiers/bayes/net/estimate/BayesNetEstimator.html" title="class in weka.classifiers.bayes.net.estimate">BayesNetEstimator</A> newBayesNetEstimator)</CODE><BR> Set the Estimator Algorithm used in calculating the CPTs</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/bayes/BayesNet.html#setOptions(java.lang.String[])">setOptions</A></B>(java.lang.String[] options)</CODE><BR> Parses a given list of options.</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/bayes/BayesNet.html#setSearchAlgorithm(weka.classifiers.bayes.net.search.SearchAlgorithm)">setSearchAlgorithm</A></B>(<A HREF="../../../weka/classifiers/bayes/net/search/SearchAlgorithm.html" title="class in weka.classifiers.bayes.net.search">SearchAlgorithm</A> newSearchAlgorithm)</CODE><BR> Set the SearchAlgorithm used in searching for network structures.</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/bayes/BayesNet.html#setUseADTree(boolean)">setUseADTree</A></B>(boolean bUseADTree)</CODE><BR> Set whether ADTree structure is used or not</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/bayes/BayesNet.html#toString()">toString</A></B>()</CODE><BR> Returns a description of 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/bayes/BayesNet.html#toXMLBIF03()">toXMLBIF03</A></B>()</CODE><BR> Returns a description of the classifier in XML BIF 0.3 format.</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/bayes/BayesNet.html#updateClassifier(weka.core.Instance)">updateClassifier</A></B>(<A HREF="../../../weka/core/Instance.html" title="class in weka.core">Instance</A> instance)</CODE><BR> Updates the classifier with the given instance.</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/bayes/BayesNet.html#useADTreeTipText()">useADTreeTipText</A></B>()</CODE><BR> </TD></TR></TABLE> <A NAME="methods_inherited_from_class_weka.classifiers.Classifier"><!-- --></A><TABLE BORDER="1" WIDTH="100%" CELLPADDING="3" CELLSPACING="0" SUMMARY=""><TR BGCOLOR="#EEEEFF" CLASS="TableSubHeadingColor"><TD><B>Methods inherited from class weka.classifiers.<A HREF="../../../weka/classifiers/Classifier.html" title="class in weka.classifiers">Classifier</A></B></TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><CODE><A HREF="../../../weka/classifiers/Classifier.html#classifyInstance(weka.core.Instance)">classifyInstance</A>, <A HREF="../../../weka/classifiers/Classifier.html#debugTipText()">debugTipText</A>, <A HREF="../../../weka/classifiers/Classifier.html#forName(java.lang.String, java.lang.String[])">forName</A>, <A HREF="../../../weka/classifiers/Classifier.html#getDebug()">getDebug</A>, <A HREF="../../../weka/classifiers/Classifier.html#makeCopies(weka.classifiers.Classifier, int)">makeCopies</A>, <A HREF="../../../weka/classifiers/Classifier.html#makeCopy(weka.classifiers.Classifier)">makeCopy</A>, <A HREF="../../../weka/classifiers/Classifier.html#setDebug(boolean)">setDebug</A></CODE></TD></TR></TABLE> <A NAME="methods_inherited_from_class_java.lang.Object"><!-- --></A><TABLE BORDER="1" WIDTH="100%" CELLPADDING="3" CELLSPACING="0" SUMMARY=""><TR BGCOLOR="#EEEEFF" CLASS="TableSubHeadingColor"><TD><B>Methods inherited from class java.lang.Object</B></TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><CODE>equals, getClass, hashCode, notify, notifyAll, wait, wait, wait</CODE></TD></TR></TABLE> <P><!-- ============ FIELD DETAIL =========== --><A NAME="field_detail"><!-- --></A><TABLE BORDER="1" WIDTH="100%" CELLPADDING="3" CELLSPACING="0" SUMMARY=""><TR BGCOLOR="#CCCCFF" CLASS="TableHeadingColor"><TD COLSPAN=1><FONT SIZE="+2"><B>Field Detail</B></FONT></TD></TR></TABLE><A NAME="m_Distributions"><!-- --></A><H3>m_Distributions</H3><PRE>public <A HREF="../../../weka/estimators/Estimator.html" title="interface in weka.estimators">Estimator</A>[][] <B>m_Distributions</B></PRE><DL><DD>The attribute estimators containing CPTs.<P><DL></DL></DL><HR><A NAME="m_Instances"><!-- --></A><H3>m_Instances</H3><PRE>public <A HREF="../../../weka/core/Instances.html" title="class in weka.core">Instances</A> <B>m_Instances</B></PRE><DL><DD>The dataset header for the purposes of printing out a semi-intelligible model<P><DL></DL></DL><!-- ========= CONSTRUCTOR DETAIL ======== --><A NAME="constructor_detail"><!-- --></A><TABLE BORDER="1" WIDTH="100%" CELLPADDING="3" CELLSPACING="0" SUMMARY=""><TR BGCOLOR="#CCCCFF" CLASS="TableHeadingColor"><TD COLSPAN=1><FONT SIZE="+2"><B>Constructor Detail</B></FONT></TD></TR></TABLE><A NAME="BayesNet()"><!-- --></A><H3>BayesNet</H3><PRE>public <B>BayesNet</B>()</PRE><DL></DL><!-- ============ METHOD DETAIL ========== --><A NAME="method_detail"><!-- --></A><TABLE BORDER="1" WIDTH="100%" CELLPADDING="3" CELLSPACING="0" SUMMARY=""><TR BGCOLOR="#CCCCFF" CLASS="TableHeadingColor"><TD COLSPAN=1><FONT SIZE="+2"><B>Method Detail</B></FONT></TD></TR></TABLE><A NAME="buildClassifier(weka.core.Instances)"><!-- --></A><H3>buildClassifier</H3><PRE>public void <B>buildClassifier</B>(<A HREF="../../../weka/core/Instances.html" title="class in weka.core">Instances</A> instances) throws java.lang.Exception</PRE><DL><DD>Generates the classifier.<P><DD><DL><DT><B>Specified by:</B><DD><CODE><A HREF="../../../weka/classifiers/Classifier.html#buildClassifier(weka.core.Instances)">buildClassifier</A></CODE> in class <CODE><A HREF="../../../weka/classifiers/Classifier.html" title="class in weka.classifiers">Classifier</A></CODE></DL></DD><DD><DL><DT><B>Parameters:</B><DD><CODE>instances</CODE> - set of instances serving as training data<DT><B>Throws:</B><DD><CODE>java.lang.Exception</CODE> - if the classifier has not been generated successfully</DL></DD></DL><HR><A NAME="initStructure()"><!-- --></A><H3>initStructure</H3><PRE>public void <B>initStructure</B>() throws java.lang.Exception</PRE><DL><DD>Init structure initializes the structure to an empty graph or a Naive Bayes graph (depending on the -N flag).<P><DD><DL></DL></DD><DD><DL><DT><B>Throws:</B><DD><CODE>java.lang.Exception</CODE></DL></DD></DL><HR><A NAME="buildStructure()"><!-- --></A><H3>buildStructure</H3><PRE>public void <B>buildStructure</B>() throws java.lang.Exception</PRE><DL><DD>buildStructure determines the network structure/graph of the network. The default behavior is creating a network where all nodes have the first node as its parent (i.e., a BayesNet that behaves like a naive Bayes classifier). This method can be overridden by derived classes to restrict the class of network structures that are acceptable.<P><DD><DL></DL></DD><DD><DL><DT><B>Throws:</B><DD><CODE>java.lang.Exception</CODE></DL></DD></DL><HR><A NAME="estimateCPTs()"><!-- --></A><H3>estimateCPTs</H3><PRE>public void <B>estimateCPTs</B>() throws java.lang.Exception</PRE><DL><DD>estimateCPTs estimates the conditional probability tables for the Bayes Net using the network structure.<P><DD><DL></DL></DD><DD><DL><DT><B>Throws:</B><DD><CODE>java.lang.Exception</CODE></DL></DD></DL><HR><A NAME="initCPTs()"><!-- --></A><H3>initCPTs</H3><PRE>public void <B>initCPTs</B>() throws java.lang.Exception</PRE><DL><DD><DL></DL></DD><DD><DL><DT><B>Throws:</B><DD><CODE>java.lang.Exception</CODE></DL></DD></DL><HR><A NAME="updateClassifier(weka.core.Instance)"><!-- --></A><H3>updateClassifier</H3><PRE>public void <B>updateClassifier</B>(<A HREF="../../../weka/core/Instance.html" title="class in weka.core">Instance</A> instance) throws java.lang.Exception</PRE><DL><DD>Updates the classifier with the given instance.<P><DD><DL></DL></DD><DD><DL><DT><B>Parameters:</B><DD><CODE>instance</CODE> - the new training instance to include in the model<DT><B>Throws:</B><DD><CODE>java.lang.Exception</CODE> - if the instance could not be incorporated in the model.</DL></DD></DL><HR><A NAME="distributionForInstance(weka.core.Instance)"><!-- --></A><H3>distributionForInstance</H3><PRE>public double[] <B>distributionForInstance</B>(<A HREF="../../../weka/core/Instance.html" title="class in weka.core">Instance</A> instance) throws java.lang.Exception</PRE><DL><DD>Calculates the class membership probabilities for the given test instance.<P><DD><DL><DT><B>Overrides:</B><DD><CODE><A HREF="../../../weka/classifiers/Classifier.html#distributionForInstance(weka.core.Instance)">distributionForInstance</A></CODE> in class <CODE><A HREF="../../../weka/classifiers/Classifier.html" title="class in weka.classifiers">Classifier</A></CODE></DL></DD><DD><DL><DT><B>Parameters:</B><DD><CODE>instance</CODE> - the instance to be classified<DT><B>Returns:</B><DD>predicted class probability distribution<DT><B>Throws:</B><DD><CODE>java.lang.Exception</CODE> - if there is a problem generating the prediction</DL></DD></DL><HR>⌨️ 快捷键说明
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