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<CODE>static <A HREF="../../../weka/core/Tag.html" title="class in weka.core">Tag</A>[]</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/bayes/BayesianLogisticRegression.html#TAGS_PRIOR">TAGS_PRIOR</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/BayesianLogisticRegression.html#Threshold">Threshold</A></B></CODE><BR> Threshold for binary classification of probabilisitic estimate</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/BayesianLogisticRegression.html#Tolerance">Tolerance</A></B></CODE><BR> Tolerance criteria for the stopping criterion.</TD></TR></TABLE> <!-- ======== CONSTRUCTOR SUMMARY ======== --><A NAME="constructor_summary"><!-- --></A><TABLE BORDER="1" WIDTH="100%" CELLPADDING="3" CELLSPACING="0" SUMMARY=""><TR BGCOLOR="#CCCCFF" CLASS="TableHeadingColor"><TH ALIGN="left" COLSPAN="2"><FONT SIZE="+2"><B>Constructor Summary</B></FONT></TH></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><CODE><B><A HREF="../../../weka/classifiers/bayes/BayesianLogisticRegression.html#BayesianLogisticRegression()">BayesianLogisticRegression</A></B>()</CODE><BR> </TD></TR></TABLE> <!-- ========== METHOD SUMMARY =========== --><A NAME="method_summary"><!-- --></A><TABLE BORDER="1" WIDTH="100%" CELLPADDING="3" CELLSPACING="0" SUMMARY=""><TR BGCOLOR="#CCCCFF" CLASS="TableHeadingColor"><TH ALIGN="left" COLSPAN="2"><FONT SIZE="+2"><B>Method Summary</B></FONT></TH></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#bigF(double, double)">bigF</A></B>(double r, double sigma)</CODE><BR> This is a convient function that defines and upper bound (Delta>0) for values of r(i) reachable by updates in the trust region.</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#buildClassifier(weka.core.Instances)">buildClassifier</A></B>(<A HREF="../../../weka/core/Instances.html" title="class in weka.core">Instances</A> data)</CODE><BR> (1) Set the data to the class attribute m_Instances. (2)Call the method initialize() to initialize the values. </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/BayesianLogisticRegression.html#classifyInstance(weka.core.Instance)">classifyInstance</A></B>(<A HREF="../../../weka/core/Instance.html" title="class in weka.core">Instance</A> instance)</CODE><BR> Classifies the given instance using the Bayesian Logistic Regression function.</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#classSgn(double)">classSgn</A></B>(double value)</CODE><BR> This class is used to mask the internal class labels.</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/BayesianLogisticRegression.html#CVBasedHyperparameter()">CVBasedHyperparameter</A></B>()</CODE><BR> Method computes the best hyperparameter value by doing cross -validation on the training data and compute the likelihood.</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#debugTipText()">debugTipText</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> <A HREF="../../../weka/core/Capabilities.html" title="class in weka.core">Capabilities</A></CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/bayes/BayesianLogisticRegression.html#getCapabilities()">getCapabilities</A></B>()</CODE><BR> This method tests what kind of data this classifier can handle.</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#getHyperparameterRange()">getHyperparameterRange</A></B>()</CODE><BR> Get the range of hyperparameter values to consider during CV-based selection.</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/BayesianLogisticRegression.html#getHyperparameterSelection()">getHyperparameterSelection</A></B>()</CODE><BR> Get 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> double</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/bayes/BayesianLogisticRegression.html#getHyperparameterValue()">getHyperparameterValue</A></B>()</CODE><BR> Get the hyperparameter value.</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/BayesianLogisticRegression.html#getLoglikeliHood(double[], weka.core.Instances)">getLoglikeliHood</A></B>(double[] betas, <A HREF="../../../weka/core/Instances.html" title="class in weka.core">Instances</A> instances)</CODE><BR> </TD></TR><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/BayesianLogisticRegression.html#getMaxIterations()">getMaxIterations</A></B>()</CODE><BR> Get 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> int</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/bayes/BayesianLogisticRegression.html#getNumFolds()">getNumFolds</A></B>()</CODE><BR> Return the number of folds for CV-based hyperparameter selection</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#getOptions()">getOptions</A></B>()</CODE><BR> Gets the current settings of the Classifier.</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/BayesianLogisticRegression.html#getPriorClass()">getPriorClass</A></B>()</CODE><BR> Get the type of prior to use.</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#getRevision()">getRevision</A></B>()</CODE><BR> Returns the revision string.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> <A HREF="../../../weka/core/TechnicalInformation.html" title="class in weka.core">TechnicalInformation</A></CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/bayes/BayesianLogisticRegression.html#getTechnicalInformation()">getTechnicalInformation</A></B>()</CODE><BR> Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.</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/BayesianLogisticRegression.html#getThreshold()">getThreshold</A></B>()</CODE><BR> Return the threshold being used.</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/BayesianLogisticRegression.html#getTolerance()">getTolerance</A></B>()</CODE><BR> Get the tolerance value</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#globalInfo()">globalInfo</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/BayesianLogisticRegression.html#hyperparameterRangeTipText()">hyperparameterRangeTipText</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#hyperparameterSelectionTipText()">hyperparameterSelectionTipText</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#hyperparameterValueTipText()">hyperparameterValueTipText</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> void</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/bayes/BayesianLogisticRegression.html#initialize()">initialize</A></B>()</CODE><BR> (1)Initialize m_Beta[j] to 0.</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#isDebug()">isDebug</A></B>()</CODE><BR> Returns true if debug is turned on.</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#isNormalizeData()">isNormalizeData</A></B>()</CODE><BR> Returns true if the data is to be normalized first</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/BayesianLogisticRegression.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 double</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/bayes/BayesianLogisticRegression.html#logisticLinkFunction(double)">logisticLinkFunction</A></B>(double r)</CODE><BR> This method computes the values for the logistic link function.</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/BayesianLogisticRegression.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> java.lang.String</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/bayes/BayesianLogisticRegression.html#maxIterationsTipText()">maxIterationsTipText</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#normalizeDataTipText()">normalizeDataTipText</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> double</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/bayes/BayesianLogisticRegression.html#normBasedHyperParameter()">normBasedHyperParameter</A></B>()</CODE><BR> This function computes the norm-based hyperparameters and stores them in the m_Hyperparameters.</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#numFoldsTipText()">numFoldsTipText</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#priorClassTipText()">priorClassTipText</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> void</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/bayes/BayesianLogisticRegression.html#setDebug(boolean)">setDebug</A></B>(boolean debugMode)</CODE><BR> Set debugging mode.</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#setHyperparameterRange(java.lang.String)">setHyperparameterRange</A></B>(java.lang.String hyperparameterRange)</CODE><BR> Set the range of hyperparameter values to consider during CV-based 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#setHyperparameterSelection(weka.core.SelectedTag)">setHyperparameterSelection</A></B>(<A HREF="../../../weka/core/SelectedTag.html" title="class in weka.core">SelectedTag</A> newMethod)</CODE><BR>⌨️ 快捷键说明
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