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Set the method used to select the hyperparameter</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/BayesianLogisticRegression.html#setHyperparameterValue(double)">setHyperparameterValue</A></B>(double hyperparameterValue)</CODE><BR> Set the hyperparameter value.</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/BayesianLogisticRegression.html#setMaxIterations(int)">setMaxIterations</A></B>(int maxIterations)</CODE><BR> Set the maximum number of iterations to perform</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/BayesianLogisticRegression.html#setNormalizeData(boolean)">setNormalizeData</A></B>(boolean normalizeData)</CODE><BR> Set whether to normalize the data or not</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/BayesianLogisticRegression.html#setNumFolds(int)">setNumFolds</A></B>(int numFolds)</CODE><BR> Set the number of folds to use for CV-based hyperparameter selection</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/BayesianLogisticRegression.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/BayesianLogisticRegression.html#setPriorClass(weka.core.SelectedTag)">setPriorClass</A></B>(<A HREF="../../../weka/core/SelectedTag.html" title="class in weka.core">SelectedTag</A> newMethod)</CODE><BR> Set the type of prior to use.</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/BayesianLogisticRegression.html#setThreshold(double)">setThreshold</A></B>(double threshold)</CODE><BR> Set the threshold to use.</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/BayesianLogisticRegression.html#setTolerance(double)">setTolerance</A></B>(double tolerance)</CODE><BR> Set the tolerance value</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>static double</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/bayes/BayesianLogisticRegression.html#sgn(double)">sgn</A></B>(double r)</CODE><BR> Sign for a given value.</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/bayes/BayesianLogisticRegression.html#stoppingCriterion()">stoppingCriterion</A></B>()</CODE><BR> This method implements the stopping criterion function.</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/BayesianLogisticRegression.html#thresholdTipText()">thresholdTipText</A></B>()</CODE><BR> Returns the tip text for this property</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/BayesianLogisticRegression.html#toleranceTipText()">toleranceTipText</A></B>()</CODE><BR> Returns the tip text for this property</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/BayesianLogisticRegression.html#toString()">toString</A></B>()</CODE><BR> Outputs the linear regression model as a string.</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#distributionForInstance(weka.core.Instance)">distributionForInstance</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></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="LogLikelihood"><!-- --></A><H3>LogLikelihood</H3><PRE>public static double[] <B>LogLikelihood</B></PRE><DL><DD>Log-likelihood values to be used to choose the best hyperparameter.<P><DL></DL></DL><HR><A NAME="InputHyperparameterValues"><!-- --></A><H3>InputHyperparameterValues</H3><PRE>public static double[] <B>InputHyperparameterValues</B></PRE><DL><DD>Set of values to be used as hyperparameter values during Cross-Validation.<P><DL></DL></DL><HR><A NAME="NormalizeData"><!-- --></A><H3>NormalizeData</H3><PRE>public boolean <B>NormalizeData</B></PRE><DL><DD>Choose whether to normalize data or not<P><DL></DL></DL><HR><A NAME="Tolerance"><!-- --></A><H3>Tolerance</H3><PRE>public double <B>Tolerance</B></PRE><DL><DD>Tolerance criteria for the stopping criterion.<P><DL></DL></DL><HR><A NAME="Threshold"><!-- --></A><H3>Threshold</H3><PRE>public double <B>Threshold</B></PRE><DL><DD>Threshold for binary classification of probabilisitic estimate<P><DL></DL></DL><HR><A NAME="GAUSSIAN"><!-- --></A><H3>GAUSSIAN</H3><PRE>public static final int <B>GAUSSIAN</B></PRE><DL><DD>Distributions available<P><DL><DT><B>See Also:</B><DD><A HREF="../../../constant-values.html#weka.classifiers.bayes.BayesianLogisticRegression.GAUSSIAN">Constant Field Values</A></DL></DL><HR><A NAME="LAPLACIAN"><!-- --></A><H3>LAPLACIAN</H3><PRE>public static final int <B>LAPLACIAN</B></PRE><DL><DL><DT><B>See Also:</B><DD><A HREF="../../../constant-values.html#weka.classifiers.bayes.BayesianLogisticRegression.LAPLACIAN">Constant Field Values</A></DL></DL><HR><A NAME="TAGS_PRIOR"><!-- --></A><H3>TAGS_PRIOR</H3><PRE>public static final <A HREF="../../../weka/core/Tag.html" title="class in weka.core">Tag</A>[] <B>TAGS_PRIOR</B></PRE><DL><DL></DL></DL><HR><A NAME="PriorClass"><!-- --></A><H3>PriorClass</H3><PRE>public int <B>PriorClass</B></PRE><DL><DD>Distribution Prior class<P><DL></DL></DL><HR><A NAME="NumFolds"><!-- --></A><H3>NumFolds</H3><PRE>public int <B>NumFolds</B></PRE><DL><DD>NumFolds for CV based Hyperparameters selection<P><DL></DL></DL><HR><A NAME="NORM_BASED"><!-- --></A><H3>NORM_BASED</H3><PRE>public static final int <B>NORM_BASED</B></PRE><DL><DD>Methods for selecting the hyperparameter value<P><DL><DT><B>See Also:</B><DD><A HREF="../../../constant-values.html#weka.classifiers.bayes.BayesianLogisticRegression.NORM_BASED">Constant Field Values</A></DL></DL><HR><A NAME="CV_BASED"><!-- --></A><H3>CV_BASED</H3><PRE>public static final int <B>CV_BASED</B></PRE><DL><DL><DT><B>See Also:</B><DD><A HREF="../../../constant-values.html#weka.classifiers.bayes.BayesianLogisticRegression.CV_BASED">Constant Field Values</A></DL></DL><HR><A NAME="SPECIFIC_VALUE"><!-- --></A><H3>SPECIFIC_VALUE</H3><PRE>public static final int <B>SPECIFIC_VALUE</B></PRE><DL><DL><DT><B>See Also:</B><DD><A HREF="../../../constant-values.html#weka.classifiers.bayes.BayesianLogisticRegression.SPECIFIC_VALUE">Constant Field Values</A></DL></DL><HR><A NAME="TAGS_HYPER_METHOD"><!-- --></A><H3>TAGS_HYPER_METHOD</H3><PRE>public static final <A HREF="../../../weka/core/Tag.html" title="class in weka.core">Tag</A>[] <B>TAGS_HYPER_METHOD</B></PRE><DL><DL></DL></DL><HR><A NAME="HyperparameterSelection"><!-- --></A><H3>HyperparameterSelection</H3><PRE>public int <B>HyperparameterSelection</B></PRE><DL><DD>Hyperparameter selection method<P><DL></DL></DL><HR><A NAME="ClassIndex"><!-- --></A><H3>ClassIndex</H3><PRE>public int <B>ClassIndex</B></PRE><DL><DD>The class index from the training data<P><DL></DL></DL><HR><A NAME="HyperparameterValue"><!-- --></A><H3>HyperparameterValue</H3><PRE>public double <B>HyperparameterValue</B></PRE><DL><DD>Best hyperparameter for test phase<P><DL></DL></DL><HR><A NAME="HyperparameterRange"><!-- --></A><H3>HyperparameterRange</H3><PRE>public java.lang.String <B>HyperparameterRange</B></PRE><DL><DD>CV Hyperparameter Range<P><DL></DL></DL><HR><A NAME="maxIterations"><!-- --></A><H3>maxIterations</H3><PRE>public int <B>maxIterations</B></PRE><DL><DD>Maximum number of iterations<P><DL></DL></DL>⌨️ 快捷键说明
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