📄 localscoresearchalgorithm.html
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<BR> Gets the current settings of the search algorithm.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> <A HREF="../../../../../../weka/core/SelectedTag.html" title="class in weka.core">SelectedTag</A></CODE></FONT></TD><TD><CODE><B><A HREF="../../../../../../weka/classifiers/bayes/net/search/local/LocalScoreSearchAlgorithm.html#getScoreType()">getScoreType</A></B>()</CODE><BR> get quality measure to be used in searching for networks.</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/search/local/LocalScoreSearchAlgorithm.html#globalInfo()">globalInfo</A></B>()</CODE><BR> This will return a string describing the search algorithm.</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/net/search/local/LocalScoreSearchAlgorithm.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> double</CODE></FONT></TD><TD><CODE><B><A HREF="../../../../../../weka/classifiers/bayes/net/search/local/LocalScoreSearchAlgorithm.html#logScore(int)">logScore</A></B>(int nType)</CODE><BR> logScore returns the log of the quality of a network (e.g.</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/search/local/LocalScoreSearchAlgorithm.html#markovBlanketClassifierTipText()">markovBlanketClassifierTipText</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/bayes/net/search/local/LocalScoreSearchAlgorithm.html#scoreTypeTipText()">scoreTypeTipText</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/net/search/local/LocalScoreSearchAlgorithm.html#setMarkovBlanketClassifier(boolean)">setMarkovBlanketClassifier</A></B>(boolean bMarkovBlanketClassifier)</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/search/local/LocalScoreSearchAlgorithm.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/net/search/local/LocalScoreSearchAlgorithm.html#setScoreType(weka.core.SelectedTag)">setScoreType</A></B>(<A HREF="../../../../../../weka/core/SelectedTag.html" title="class in weka.core">SelectedTag</A> newScoreType)</CODE><BR> set quality measure to be used in searching for networks.</TD></TR></TABLE> <A NAME="methods_inherited_from_class_weka.classifiers.bayes.net.search.SearchAlgorithm"><!-- --></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.net.search.<A HREF="../../../../../../weka/classifiers/bayes/net/search/SearchAlgorithm.html" title="class in weka.classifiers.bayes.net.search">SearchAlgorithm</A></B></TH></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><CODE><A HREF="../../../../../../weka/classifiers/bayes/net/search/SearchAlgorithm.html#initAsNaiveBayesTipText()">initAsNaiveBayesTipText</A>, <A HREF="../../../../../../weka/classifiers/bayes/net/search/SearchAlgorithm.html#maxNrOfParentsTipText()">maxNrOfParentsTipText</A>, <A HREF="../../../../../../weka/classifiers/bayes/net/search/SearchAlgorithm.html#toString()">toString</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><!-- ============ FIELD DETAIL =========== --><A NAME="field_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>Field Detail</B></FONT></TH></TR></TABLE><A NAME="TAGS_SCORE_TYPE"><!-- --></A><H3>TAGS_SCORE_TYPE</H3><PRE>public static final <A HREF="../../../../../../weka/core/Tag.html" title="class in weka.core">Tag</A>[] <B>TAGS_SCORE_TYPE</B></PRE><DL><DD>the score types<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"><TH ALIGN="left" COLSPAN="1"><FONT SIZE="+2"><B>Constructor Detail</B></FONT></TH></TR></TABLE><A NAME="LocalScoreSearchAlgorithm()"><!-- --></A><H3>LocalScoreSearchAlgorithm</H3><PRE>public <B>LocalScoreSearchAlgorithm</B>()</PRE><DL><DD>default constructor<P></DL><HR><A NAME="LocalScoreSearchAlgorithm(weka.classifiers.bayes.BayesNet, weka.core.Instances)"><!-- --></A><H3>LocalScoreSearchAlgorithm</H3><PRE>public <B>LocalScoreSearchAlgorithm</B>(<A HREF="../../../../../../weka/classifiers/bayes/BayesNet.html" title="class in weka.classifiers.bayes">BayesNet</A> bayesNet, <A HREF="../../../../../../weka/core/Instances.html" title="class in weka.core">Instances</A> instances)</PRE><DL><DD>constructor<P><DL><DT><B>Parameters:</B><DD><CODE>bayesNet</CODE> - the network<DD><CODE>instances</CODE> - the data</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="logScore(int)"><!-- --></A><H3>logScore</H3><PRE>public double <B>logScore</B>(int nType)</PRE><DL><DD>logScore returns the log of the quality of a network (e.g. the posterior probability of the network, or the MDL value).<P><DD><DL><DT><B>Parameters:</B><DD><CODE>nType</CODE> - score type (Bayes, MDL, etc) to calculate score with<DT><B>Returns:</B><DD>log score.</DL></DD></DL><HR><A NAME="buildStructure(weka.classifiers.bayes.BayesNet, weka.core.Instances)"><!-- --></A><H3>buildStructure</H3><PRE>public void <B>buildStructure</B>(<A HREF="../../../../../../weka/classifiers/bayes/BayesNet.html" title="class in weka.classifiers.bayes">BayesNet</A> bayesNet, <A HREF="../../../../../../weka/core/Instances.html" title="class in weka.core">Instances</A> instances) throws java.lang.Exception</PRE><DL><DD>buildStructure determines the network structure/graph of the network with the K2 algorithm, restricted by its initial structure (which can be an empty graph, or a Naive Bayes graph.<P><DD><DL><DT><B>Overrides:</B><DD><CODE><A HREF="../../../../../../weka/classifiers/bayes/net/search/SearchAlgorithm.html#buildStructure(weka.classifiers.bayes.BayesNet, weka.core.Instances)">buildStructure</A></CODE> in class <CODE><A HREF="../../../../../../weka/classifiers/bayes/net/search/SearchAlgorithm.html" title="class in weka.classifiers.bayes.net.search">SearchAlgorithm</A></CODE></DL></DD><DD><DL><DT><B>Parameters:</B><DD><CODE>bayesNet</CODE> - the network<DD><CODE>instances</CODE> - the data to use<DT><B>Throws:</B><DD><CODE>java.lang.Exception</CODE> - if something goes wrong</DL></DD></DL><HR><A NAME="calcNodeScore(int)"><!-- --></A><H3>calcNodeScore</H3><PRE>public double <B>calcNodeScore</B>(int nNode)</PRE><DL><DD>Calc Node Score for given parent set<P><DD><DL><DT><B>Parameters:</B><DD><CODE>nNode</CODE> - node for which the score is calculate<DT><B>Returns:</B><DD>log score</DL></DD></DL><HR><A NAME="calcScoreWithExtraParent(int, int)"><!-- --></A><H3>calcScoreWithExtraParent</H3><PRE>public double <B>calcScoreWithExtraParent</B>(int nNode, int nCandidateParent)</PRE><DL><DD>Calc Node Score With AddedParent<P><DD><DL><DT><B>Parameters:</B><DD><CODE>nNode</CODE> - node for which the score is calculate<DD><CODE>nCandidateParent</CODE> - candidate parent to add to the existing parent set<DT><B>Returns:</B><DD>log score</DL></DD></DL><HR><A NAME="calcScoreWithMissingParent(int, int)"><!-- --></A><H3>calcScoreWithMissingParent</H3><PRE>public double <B>calcScoreWithMissingParent</B>(int nNode, int nCandidateParent)</PRE><DL><DD>Calc Node Score With Parent Deleted⌨️ 快捷键说明
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