📄 editablebayesnet.html
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<A HREF="../../../../weka/core/FastVector.html" title="class in weka.core">FastVector</A> nPosY)</CODE><BR> set positions of all nodes</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/net/EditableBayesNet.html#main(java.lang.String[])">main</A></B>(java.lang.String[] args)</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/net/EditableBayesNet.html#paste(java.lang.String)">paste</A></B>(java.lang.String sXML)</CODE><BR> Apply paste operation with XMLBIF fragment.</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/net/EditableBayesNet.html#redo()">redo</A></B>()</CODE><BR> redo the last edit action performed on the network.</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/net/EditableBayesNet.html#renameNodeValue(int, java.lang.String, java.lang.String)">renameNodeValue</A></B>(int nTargetNode, java.lang.String sValue, java.lang.String sNewValue)</CODE><BR> change the name of a value of a node</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/net/EditableBayesNet.html#setData(weka.core.Instances)">setData</A></B>(<A HREF="../../../../weka/core/Instances.html" title="class in weka.core">Instances</A> instances)</CODE><BR> Assuming a network structure is defined and we want to learn from data, the data set must be put if correct order first and possibly discretized/missing values filled in before proceeding to CPT learning.</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/net/EditableBayesNet.html#setDistribution(int, double[][])">setDistribution</A></B>(int nTargetNode, double[][] P)</CODE><BR> specify distribution of a node</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/net/EditableBayesNet.html#setDistribution(java.lang.String, double[][])">setDistribution</A></B>(java.lang.String sName, double[][] P)</CODE><BR> specify distribution of a node</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/net/EditableBayesNet.html#setEvidence(int, int)">setEvidence</A></B>(int iNode, int iValue)</CODE><BR> set evidence state of a node.</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/net/EditableBayesNet.html#setMargin(int, double[])">setMargin</A></B>(int iNode, double[] fMarginP)</CODE><BR> set marginal distibution for a node</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/net/EditableBayesNet.html#setNodeName(int, java.lang.String)">setNodeName</A></B>(int nTargetNode, java.lang.String sName)</CODE><BR> change the name of a node</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/net/EditableBayesNet.html#setPosition(int, int, int)">setPosition</A></B>(int iNode, int nX, int nY)</CODE><BR> set position of node</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/net/EditableBayesNet.html#setPosition(int, int, int, weka.core.FastVector)">setPosition</A></B>(int nNode, int nX, int nY, <A HREF="../../../../weka/core/FastVector.html" title="class in weka.core">FastVector</A> nodes)</CODE><BR> Set position of node.</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/net/EditableBayesNet.html#spaceHorizontal(weka.core.FastVector)">spaceHorizontal</A></B>(<A HREF="../../../../weka/core/FastVector.html" title="class in weka.core">FastVector</A> nodes)</CODE><BR> space out set of nodes evenly between left and right most node in the list</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/net/EditableBayesNet.html#spaceVertical(weka.core.FastVector)">spaceVertical</A></B>(<A HREF="../../../../weka/core/FastVector.html" title="class in weka.core">FastVector</A> nodes)</CODE><BR> space out set of nodes evenly between top and bottom most node in the list</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/net/EditableBayesNet.html#toXMLBIF03()">toXMLBIF03</A></B>()</CODE><BR> returns network in XMLBIF format</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/net/EditableBayesNet.html#toXMLBIF03(weka.core.FastVector)">toXMLBIF03</A></B>(<A HREF="../../../../weka/core/FastVector.html" title="class in weka.core">FastVector</A> nodes)</CODE><BR> return fragment of network in XMLBIF format</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/net/EditableBayesNet.html#undo()">undo</A></B>()</CODE><BR> undo the last edit action performed on the network.</TD></TR></TABLE> <A NAME="methods_inherited_from_class_weka.classifiers.bayes.BayesNet"><!-- --></A><TABLE BORDER="1" WIDTH="100%" CELLPADDING="3" CELLSPACING="0" SUMMARY=""><TR BGCOLOR="#EEEEFF" CLASS="TableSubHeadingColor"><TH ALIGN="left"><B>Methods inherited from class weka.classifiers.bayes.<A HREF="../../../../weka/classifiers/bayes/BayesNet.html" title="class in weka.classifiers.bayes">BayesNet</A></B></TH></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><CODE><A HREF="../../../../weka/classifiers/bayes/BayesNet.html#BIFFileTipText()">BIFFileTipText</A>, <A HREF="../../../../weka/classifiers/bayes/BayesNet.html#buildClassifier(weka.core.Instances)">buildClassifier</A>, <A HREF="../../../../weka/classifiers/bayes/BayesNet.html#buildStructure()">buildStructure</A>, <A HREF="../../../../weka/classifiers/bayes/BayesNet.html#countsForInstance(weka.core.Instance)">countsForInstance</A>, <A HREF="../../../../weka/classifiers/bayes/BayesNet.html#distributionForInstance(weka.core.Instance)">distributionForInstance</A>, <A HREF="../../../../weka/classifiers/bayes/BayesNet.html#enumerateMeasures()">enumerateMeasures</A>, <A HREF="../../../../weka/classifiers/bayes/BayesNet.html#estimateCPTs()">estimateCPTs</A>, <A HREF="../../../../weka/classifiers/bayes/BayesNet.html#estimatorTipText()">estimatorTipText</A>, <A HREF="../../../../weka/classifiers/bayes/BayesNet.html#getADTree()">getADTree</A>, <A HREF="../../../../weka/classifiers/bayes/BayesNet.html#getBIFFile()">getBIFFile</A>, <A HREF="../../../../weka/classifiers/bayes/BayesNet.html#getBIFHeader()">getBIFHeader</A>, <A HREF="../../../../weka/classifiers/bayes/BayesNet.html#getCapabilities()">getCapabilities</A>, <A HREF="../../../../weka/classifiers/bayes/BayesNet.html#getCardinality(int)">getCardinality</A>, <A HREF="../../../../weka/classifiers/bayes/BayesNet.html#getDistributions()">getDistributions</A>, <A HREF="../../../../weka/classifiers/bayes/BayesNet.html#getEstimator()">getEstimator</A>, <A HREF="../../../../weka/classifiers/bayes/BayesNet.html#getMeasure(java.lang.String)">getMeasure</A>, <A HREF="../../../../weka/classifiers/bayes/BayesNet.html#getName()">getName</A>, <A HREF="../../../../weka/classifiers/bayes/BayesNet.html#getNodeName(int)">getNodeName</A>, <A HREF="../../../../weka/classifiers/bayes/BayesNet.html#getNodeValue(int, int)">getNodeValue</A>, <A HREF="../../../../weka/classifiers/bayes/BayesNet.html#getNrOfNodes()">getNrOfNodes</A>, <A HREF="../../../../weka/classifiers/bayes/BayesNet.html#getNrOfParents(int)">getNrOfParents</A>, <A HREF="../../../../weka/classifiers/bayes/BayesNet.html#getOptions()">getOptions</A>, <A HREF="../../../../weka/classifiers/bayes/BayesNet.html#getParent(int, int)">getParent</A>, <A HREF="../../../../weka/classifiers/bayes/BayesNet.html#getParentCardinality(int)">getParentCardinality</A>, <A HREF="../../../../weka/classifiers/bayes/BayesNet.html#getParentSet(int)">getParentSet</A>, <A HREF="../../../../weka/classifiers/bayes/BayesNet.html#getParentSets()">getParentSets</A>, <A HREF="../../../../weka/classifiers/bayes/BayesNet.html#getProbability(int, int, int)">getProbability</A>, <A HREF="../../../../weka/classifiers/bayes/BayesNet.html#getSearchAlgorithm()">getSearchAlgorithm</A>, <A HREF="../../../../weka/classifiers/bayes/BayesNet.html#getUseADTree()">getUseADTree</A>, <A HREF="../../../../weka/classifiers/bayes/BayesNet.html#globalInfo()">globalInfo</A>, <A HREF="../../../../weka/classifiers/bayes/BayesNet.html#graph()">graph</A>, <A HREF="../../../../weka/classifiers/bayes/BayesNet.html#graphType()">graphType</A>, <A HREF="../../../../weka/classifiers/bayes/BayesNet.html#initCPTs()">initCPTs</A>, <A HREF="../../../../weka/classifiers/bayes/BayesNet.html#initStructure()">initStructure</A>, <A HREF="../../../../weka/classifiers/bayes/BayesNet.html#listOptions()">listOptions</A>, <A HREF="../../../../weka/classifiers/bayes/BayesNet.html#measureAICScore()">measureAICScore</A>, <A HREF="../../../../weka/classifiers/bayes/BayesNet.html#measureBayesScore()">measureBayesScore</A>, <A HREF="../../../../weka/classifiers/bayes/BayesNet.html#measureBDeuScore()">measureBDeuScore</A>, <A HREF="../../../../weka/classifiers/bayes/BayesNet.html#measureDivergence()">measureDivergence</A>, <A HREF="../../../../weka/classifiers/bayes/BayesNet.html#measureEntropyScore()">measureEntropyScore</A>, <A HREF="../../../../weka/classifiers/bayes/BayesNet.html#measureExtraArcs()">measureExtraArcs</A>, <A HREF="../../../../weka/classifiers/bayes/BayesNet.html#measureMDLScore()">measureMDLScore</A>, <A HREF="../../../../weka/classifiers/bayes/BayesNet.html#measureMissingArcs()">measureMissingArcs</A>, <A HREF="../../../../weka/classifiers/bayes/BayesNet.html#measureReversedArcs()">measureReversedArcs</A>, <A HREF="../../../../weka/classifiers/bayes/BayesNet.html#partitionOptions(java.lang.String[])">partitionOptions</A>, <A HREF="../../../../weka/classifiers/bayes/BayesNet.html#searchAlgorithmTipText()">searchAlgorithmTipText</A>, <A HREF="../../../../weka/classifiers/bayes/BayesNet.html#setBIFFile(java.lang.String)">setBIFFile</A>, <A HREF="../../../../weka/classifiers/bayes/BayesNet.html#setEstimator(weka.classifiers.bayes.net.estimate.BayesNetEstimator)">setEstimator</A>, <A HREF="../../../../weka/classifiers/bayes/BayesNet.html#setOptions(java.lang.String[])">setOptions</A>, <A HREF="../../../../weka/classifiers/bayes/BayesNet.html#setSearchAlgorithm(weka.classifiers.bayes.net.search.SearchAlgorithm)">setSearchAlgorithm</A>, <A HREF="../../../../weka/classifiers/bayes/BayesNet.html#setUseADTree(boolean)">setUseADTree</A>, <A HREF="../../../../weka/classifiers/bayes/BayesNet.html#toString()">toString</A>, <A HREF="../../../../weka/classifiers/bayes/BayesNet.html#updateClassifier(weka.core.Instance)">updateClassifier</A>, <A HREF="../../../../weka/classifiers/bayes/BayesNet.html#useADTreeTipText()">useADTreeTipText</A></CODE></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"><TH ALIGN="left"><B>Methods inherited from class weka.classifiers.<A HREF="../../../../weka/classifiers/Classifier.html" title="class in weka.classifiers">Classifier</A></B></TH></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"><TH ALIGN="left"><B>Methods inherited from class java.lang.Object</B></TH></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><CODE>equals, getClass, hashCode, notify, notifyAll, wait, wait, wait</CODE></TD></TR></TABLE> <P><!-- ========= CONSTRUCTOR DETAIL ======== --><A NAME="constructor_detail"><!-- --></A><TABLE BORDER="1" WIDTH="100%" CELLPADDING="3" CELLSPACING="0" SUMMARY=""><TR BGCOLOR="#CCCCFF" CLASS="TableHeadingColor"><TH ALIGN="left" COLSPAN="1"><FONT SIZE="+2"><B>Constructor Detail</B></FONT></TH></TR></TABLE><A NAME="EditableBayesNet()"><!-- --></A><H3>EditableBayesNet</H3><PRE>public <B>EditableBayesNet</B>()</PRE><DL><DD>standard constructor *<P></DL><HR><A NAME="EditableBayesNet(weka.core.Instances)"><!-- --></A><H3>EditableBayesNet</H3><PRE>public <B>EditableBayesNet</B>(<A HREF="../../../../weka/core/Instances.html" title="class in weka.core">Instances</A> instances)</PRE><DL><DD>constructor, creates empty network with nodes based on the attributes in a data set<P></DL><HR><A NAME="EditableBayesNet(weka.classifiers.bayes.net.BIFReader)"><!-- --></A><H3>EditableBayesNet</H3><PRE>public <B>EditableBayesNet</B>(<A HREF="../../../../weka/classifiers/bayes/net/BIFReader.html" title="class in weka.classifiers.bayes.net">BIFReader</A> other)</PRE><DL><DD>constructor, copies Bayesian network structure from a Bayesian network encapsulated in a BIFReader<P></DL><HR><A NAME="EditableBayesNet(boolean)"><!-- --></A><H3>EditableBayesNet</H3><PRE>public <B>EditableBayesNet</B>(boolean bSetInstances)</PRE><DL><DD>constructor that potentially initializes instances as well<P><DL><DT><B>Parameters:</B><DD><CODE>bSetInstances</CODE> - flag indicating whether to initialize instances or not</DL></DL><!-- ============ METHOD DETAIL ========== --><A NAME="method_detail"><!-- --></A><TABLE BORDER="1" WIDTH="100%" CELLPADDING="3" CELLSPACING="0" SUMMARY=""><TR BGCOLOR="#CCCCFF" CLASS="TableHeadingColor"><TH ALIGN="left" COLSPAN="1"><FONT SIZE="+2"><B>Method Detail</B></FONT></TH></TR></TABLE><A NAME="setData(weka.core.Instances)"><!-- --></A><H3>setData</H3><PRE>public void <B>setData</B>(<A HREF="../../../../weka/core/Instances.html" title="class in weka.core">Instances</A> instances) throws java.lang.Exception</PRE><DL><DD>Assuming a network structure is defined and we want to learn from data, the data set must be put if correct order first and possibly discretized/missing values filled in before proceeding to CPT learning.<P><DD><DL><DT><B>Parameters:</B><DD><CODE>instances</CODE> - data set to learn from<DT><B>Throws:</B><DD><CODE>when</CODE> - data sets are not compatible, e.g., a variable is missing or a variable has different nr of values.<DD><CODE>java.lang.Exception</CODE></DL></DD></DL><HR><A NAME="getNode2(java.lang.String)"><!-- --></A><H3>getNode2</H3><PRE>public int <B>getNode2</B>(java.lang.String sNodeName)</PRE><DL><DD>returns index of node with given name, or -1 if no such node exists<P><DD><DL>⌨️ 快捷键说明
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