globalscoresearchalgorithm.html

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<CODE>&nbsp;java.lang.String</CODE></FONT></TD>
<TD><CODE><B><A HREF="../../../../../../weka/classifiers/bayes/net/search/global/GlobalScoreSearchAlgorithm.html#globalInfo()">globalInfo</A></B>()</CODE>

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&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;This will return a string describing the search algorithm.</TD>
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<TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1">
<CODE>&nbsp;double</CODE></FONT></TD>
<TD><CODE><B><A HREF="../../../../../../weka/classifiers/bayes/net/search/global/GlobalScoreSearchAlgorithm.html#kFoldCV(weka.classifiers.bayes.BayesNet, int)">kFoldCV</A></B>(<A HREF="../../../../../../weka/classifiers/bayes/BayesNet.html" title="class in weka.classifiers.bayes">BayesNet</A>&nbsp;bayesNet,
        int&nbsp;nNrOfFolds)</CODE>

<BR>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;kFoldCV uses k-fold cross validation to measure the accuracy of a Bayes
 network classifier.</TD>
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<TR BGCOLOR="white" CLASS="TableRowColor">
<TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1">
<CODE>&nbsp;double</CODE></FONT></TD>
<TD><CODE><B><A HREF="../../../../../../weka/classifiers/bayes/net/search/global/GlobalScoreSearchAlgorithm.html#leaveOneOutCV(weka.classifiers.bayes.BayesNet)">leaveOneOutCV</A></B>(<A HREF="../../../../../../weka/classifiers/bayes/BayesNet.html" title="class in weka.classifiers.bayes">BayesNet</A>&nbsp;bayesNet)</CODE>

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&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;LeaveOneOutCV returns the accuracy calculated using Leave One Out
 cross validation.</TD>
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<TR BGCOLOR="white" CLASS="TableRowColor">
<TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1">
<CODE>&nbsp;java.util.Enumeration</CODE></FONT></TD>
<TD><CODE><B><A HREF="../../../../../../weka/classifiers/bayes/net/search/global/GlobalScoreSearchAlgorithm.html#listOptions()">listOptions</A></B>()</CODE>

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&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Returns an enumeration describing the available options</TD>
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<TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1">
<CODE>&nbsp;void</CODE></FONT></TD>
<TD><CODE><B><A HREF="../../../../../../weka/classifiers/bayes/net/search/global/GlobalScoreSearchAlgorithm.html#setCVType(weka.core.SelectedTag)">setCVType</A></B>(<A HREF="../../../../../../weka/core/SelectedTag.html" title="class in weka.core">SelectedTag</A>&nbsp;newCVType)</CODE>

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&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;set cross validation strategy to be used in searching for networks.</TD>
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<TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1">
<CODE>&nbsp;void</CODE></FONT></TD>
<TD><CODE><B><A HREF="../../../../../../weka/classifiers/bayes/net/search/global/GlobalScoreSearchAlgorithm.html#setOptions(java.lang.String[])">setOptions</A></B>(java.lang.String[]&nbsp;options)</CODE>

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&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Parses a given list of options.</TD>
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<TR BGCOLOR="white" CLASS="TableRowColor">
<TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1">
<CODE>&nbsp;void</CODE></FONT></TD>
<TD><CODE><B><A HREF="../../../../../../weka/classifiers/bayes/net/search/global/GlobalScoreSearchAlgorithm.html#setUseProb(boolean)">setUseProb</A></B>(boolean&nbsp;useProb)</CODE>

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<TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1">
<CODE>&nbsp;java.lang.String</CODE></FONT></TD>
<TD><CODE><B><A HREF="../../../../../../weka/classifiers/bayes/net/search/global/GlobalScoreSearchAlgorithm.html#useProbTipText()">useProbTipText</A></B>()</CODE>

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&nbsp;<A NAME="methods_inherited_from_class_weka.classifiers.bayes.net.search.SearchAlgorithm"><!-- --></A>
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<TD><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></TD>
</TR>
<TR BGCOLOR="white" CLASS="TableRowColor">
<TD><CODE><A HREF="../../../../../../weka/classifiers/bayes/net/search/SearchAlgorithm.html#buildStructure(weka.classifiers.bayes.BayesNet, weka.core.Instances)">buildStructure</A>, <A HREF="../../../../../../weka/classifiers/bayes/net/search/SearchAlgorithm.html#getMarkovBlanketClassifier()">getMarkovBlanketClassifier</A>, <A HREF="../../../../../../weka/classifiers/bayes/net/search/SearchAlgorithm.html#initAsNaiveBayesTipText()">initAsNaiveBayesTipText</A>, <A HREF="../../../../../../weka/classifiers/bayes/net/search/SearchAlgorithm.html#markovBlanketClassifierTipText()">markovBlanketClassifierTipText</A>, <A HREF="../../../../../../weka/classifiers/bayes/net/search/SearchAlgorithm.html#maxNrOfParentsTipText()">maxNrOfParentsTipText</A>, <A HREF="../../../../../../weka/classifiers/bayes/net/search/SearchAlgorithm.html#setMarkovBlanketClassifier(boolean)">setMarkovBlanketClassifier</A>, <A HREF="../../../../../../weka/classifiers/bayes/net/search/SearchAlgorithm.html#toString()">toString</A></CODE></TD>
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<TD><B>Methods inherited from class java.lang.Object</B></TD>
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<TD><CODE>equals, getClass, hashCode, notify, notifyAll, wait, wait, wait</CODE></TD>
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<B>Field Detail</B></FONT></TD>
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<A NAME="TAGS_CV_TYPE"><!-- --></A><H3>
TAGS_CV_TYPE</H3>
<PRE>
public static final <A HREF="../../../../../../weka/core/Tag.html" title="class in weka.core">Tag</A>[] <B>TAGS_CV_TYPE</B></PRE>
<DL>
<DL>
</DL>
</DL>

<!-- ========= CONSTRUCTOR DETAIL ======== -->

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<B>Constructor Detail</B></FONT></TD>
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<A NAME="GlobalScoreSearchAlgorithm()"><!-- --></A><H3>
GlobalScoreSearchAlgorithm</H3>
<PRE>
public <B>GlobalScoreSearchAlgorithm</B>()</PRE>
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<A NAME="calcScore(weka.classifiers.bayes.BayesNet)"><!-- --></A><H3>
calcScore</H3>
<PRE>
public double <B>calcScore</B>(<A HREF="../../../../../../weka/classifiers/bayes/BayesNet.html" title="class in weka.classifiers.bayes">BayesNet</A>&nbsp;bayesNet)
                 throws java.lang.Exception</PRE>
<DL>
<DD>performCV returns the accuracy calculated using cross validation.  
 The dataset used is m_Instances associated with the Bayes Network.
<P>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>bayesNet</CODE> - : Bayes Network containing structure to evaluate
<DT><B>Returns:</B><DD>accuracy (in interval 0..1) measured using cv.
<DT><B>Throws:</B>
<DD><CODE>java.lang.Exception</CODE> - whn m_nCVType is invalided + exceptions passed on by updateClassifier</DL>
</DD>
</DL>
<HR>

<A NAME="calcScoreWithExtraParent(int, int)"><!-- --></A><H3>
calcScoreWithExtraParent</H3>
<PRE>
public double <B>calcScoreWithExtraParent</B>(int&nbsp;nNode,
                                       int&nbsp;nCandidateParent)
                                throws java.lang.Exception</PRE>
<DL>
<DD>Calc Node Score With Added Parent
<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
<DT><B>Throws:</B>
<DD><CODE>java.lang.Exception</CODE></DL>
</DD>
</DL>
<HR>

<A NAME="calcScoreWithMissingParent(int, int)"><!-- --></A><H3>
calcScoreWithMissingParent</H3>
<PRE>
public double <B>calcScoreWithMissingParent</B>(int&nbsp;nNode,
                                         int&nbsp;nCandidateParent)
                                  throws java.lang.Exception</PRE>
<DL>
<DD>Calc Node Score With Parent Deleted
<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 delete from the existing parent set
<DT><B>Returns:</B><DD>log score
<DT><B>Throws:</B>
<DD><CODE>java.lang.Exception</CODE></DL>
</DD>
</DL>
<HR>

<A NAME="calcScoreWithReversedParent(int, int)"><!-- --></A><H3>
calcScoreWithReversedParent</H3>
<PRE>
public double <B>calcScoreWithReversedParent</B>(int&nbsp;nNode,
                                          int&nbsp;nCandidateParent)
                                   throws java.lang.Exception</PRE>
<DL>
<DD>Calc Node Score With Arrow reversed
<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 delete from the existing parent set
<DT><B>Returns:</B><DD>log score
<DT><B>Throws:</B>
<DD><CODE>java.lang.Exception</CODE></DL>
</DD>
</DL>
<HR>

<A NAME="leaveOneOutCV(weka.classifiers.bayes.BayesNet)"><!-- --></A><H3>
leaveOneOutCV</H3>
<PRE>
public double <B>leaveOneOutCV</B>(<A HREF="../../../../../../weka/classifiers/bayes/BayesNet.html" title="class in weka.classifiers.bayes">BayesNet</A>&nbsp;bayesNet)
                     throws java.lang.Exception</PRE>
<DL>
<DD>LeaveOneOutCV returns the accuracy calculated using Leave One Out
 cross validation. The dataset used is m_Instances associated with
 the Bayes Network.
<P>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>bayesNet</CODE> - : Bayes Network containing structure to evaluate
<DT><B>Returns:</B><DD>accuracy (in interval 0..1) measured using leave one out cv.
<DT><B>Throws:</B>
<DD><CODE>java.lang.Exception</CODE> - passed on by updateClassifier</DL>
</DD>
</DL>
<HR>

<A NAME="cumulativeCV(weka.classifiers.bayes.BayesNet)"><!-- --></A><H3>
cumulativeCV</H3>
<PRE>
public double <B>cumulativeCV</B>(<A HREF="../../../../../../weka/classifiers/bayes/BayesNet.html" title="class in weka.classifiers.bayes">BayesNet</A>&nbsp;bayesNet)
                    throws java.lang.Exception</PRE>
<DL>
<DD>CumulativeCV returns the accuracy calculated using cumulative
 cross validation. The idea is to run through the data set and