📄 evaluation.html
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</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/Evaluation.html#crossValidateModel(weka.classifiers.Classifier, weka.core.Instances, int, java.util.Random, java.lang.Object...)">crossValidateModel</A></B>(<A HREF="../../weka/classifiers/Classifier.html" title="class in weka.classifiers">Classifier</A> classifier, <A HREF="../../weka/core/Instances.html" title="class in weka.core">Instances</A> data, int numFolds, java.util.Random random, java.lang.Object... forPredictionsPrinting)</CODE><BR> Performs a (stratified if class is nominal) cross-validation for a classifier on a set of instances.</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/Evaluation.html#crossValidateModel(java.lang.String, weka.core.Instances, int, java.lang.String[], java.util.Random)">crossValidateModel</A></B>(java.lang.String classifierString, <A HREF="../../weka/core/Instances.html" title="class in weka.core">Instances</A> data, int numFolds, java.lang.String[] options, java.util.Random random)</CODE><BR> Performs a (stratified if class is nominal) cross-validation for a classifier on a set of instances.</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/Evaluation.html#equals(java.lang.Object)">equals</A></B>(java.lang.Object obj)</CODE><BR> Tests whether the current evaluation object is equal to another evaluation object</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/Evaluation.html#errorRate()">errorRate</A></B>()</CODE><BR> Returns the estimated error rate or the root mean squared error (if the class is numeric).</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/Evaluation.html#evaluateModel(weka.classifiers.Classifier, weka.core.Instances, java.lang.Object...)">evaluateModel</A></B>(<A HREF="../../weka/classifiers/Classifier.html" title="class in weka.classifiers">Classifier</A> classifier, <A HREF="../../weka/core/Instances.html" title="class in weka.core">Instances</A> data, java.lang.Object... forPredictionsPrinting)</CODE><BR> Evaluates the classifier on a given set of instances.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>static java.lang.String</CODE></FONT></TD><TD><CODE><B><A HREF="../../weka/classifiers/Evaluation.html#evaluateModel(weka.classifiers.Classifier, java.lang.String[])">evaluateModel</A></B>(<A HREF="../../weka/classifiers/Classifier.html" title="class in weka.classifiers">Classifier</A> classifier, java.lang.String[] options)</CODE><BR> Evaluates a classifier with the options given in an array of strings.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>static java.lang.String</CODE></FONT></TD><TD><CODE><B><A HREF="../../weka/classifiers/Evaluation.html#evaluateModel(java.lang.String, java.lang.String[])">evaluateModel</A></B>(java.lang.String classifierString, java.lang.String[] options)</CODE><BR> Evaluates a classifier with the options given in an array of strings.</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/Evaluation.html#evaluateModelOnce(weka.classifiers.Classifier, weka.core.Instance)">evaluateModelOnce</A></B>(<A HREF="../../weka/classifiers/Classifier.html" title="class in weka.classifiers">Classifier</A> classifier, <A HREF="../../weka/core/Instance.html" title="class in weka.core">Instance</A> instance)</CODE><BR> Evaluates the classifier on a single instance.</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/Evaluation.html#evaluateModelOnce(double[], weka.core.Instance)">evaluateModelOnce</A></B>(double[] dist, <A HREF="../../weka/core/Instance.html" title="class in weka.core">Instance</A> instance)</CODE><BR> Evaluates the supplied distribution on a single instance.</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/Evaluation.html#evaluateModelOnce(double, weka.core.Instance)">evaluateModelOnce</A></B>(double prediction, <A HREF="../../weka/core/Instance.html" title="class in weka.core">Instance</A> instance)</CODE><BR> Evaluates the supplied prediction on a single instance.</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/Evaluation.html#evaluateModelOnceAndRecordPrediction(weka.classifiers.Classifier, weka.core.Instance)">evaluateModelOnceAndRecordPrediction</A></B>(<A HREF="../../weka/classifiers/Classifier.html" title="class in weka.classifiers">Classifier</A> classifier, <A HREF="../../weka/core/Instance.html" title="class in weka.core">Instance</A> instance)</CODE><BR> Evaluates the classifier on a single instance and records the prediction (if the class is nominal).</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/Evaluation.html#evaluateModelOnceAndRecordPrediction(double[], weka.core.Instance)">evaluateModelOnceAndRecordPrediction</A></B>(double[] dist, <A HREF="../../weka/core/Instance.html" title="class in weka.core">Instance</A> instance)</CODE><BR> Evaluates the supplied distribution on a single instance.</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/Evaluation.html#falseNegativeRate(int)">falseNegativeRate</A></B>(int classIndex)</CODE><BR> Calculate the false negative rate with respect to a particular class.</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/Evaluation.html#falsePositiveRate(int)">falsePositiveRate</A></B>(int classIndex)</CODE><BR> Calculate the false positive rate with respect to a particular class.</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/Evaluation.html#fMeasure(int)">fMeasure</A></B>(int classIndex)</CODE><BR> Calculate the F-Measure with respect to a particular class.</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/Evaluation.html#getClassPriors()">getClassPriors</A></B>()</CODE><BR> Get the current weighted class counts</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/Evaluation.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> double</CODE></FONT></TD><TD><CODE><B><A HREF="../../weka/classifiers/Evaluation.html#incorrect()">incorrect</A></B>()</CODE><BR> Gets the number of instances incorrectly classified (that is, for which an incorrect prediction was made).</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/Evaluation.html#kappa()">kappa</A></B>()</CODE><BR> Returns value of kappa statistic if class is nominal.</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/Evaluation.html#KBInformation()">KBInformation</A></B>()</CODE><BR> Return the total Kononenko & Bratko Information score in bits</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/Evaluation.html#KBMeanInformation()">KBMeanInformation</A></B>()</CODE><BR> Return the Kononenko & Bratko Information score in bits per instance.</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/Evaluation.html#KBRelativeInformation()">KBRelativeInformation</A></B>()</CODE><BR> Return the Kononenko & Bratko Relative Information score</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/Evaluation.html#main(java.lang.String[])">main</A></B>(java.lang.String[] args)</CODE><BR> A test method for this class.</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/Evaluation.html#meanAbsoluteError()">meanAbsoluteError</A></B>()</CODE><BR> Returns the mean absolute error.</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/Evaluation.html#meanPriorAbsoluteError()">meanPriorAbsoluteError</A></B>()</CODE><BR> Returns the mean absolute error of the prior.</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/Evaluation.html#numFalseNegatives(int)">numFalseNegatives</A></B>(int classIndex)</CODE><BR> Calculate number of false negatives with respect to a particular class.</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/Evaluation.html#numFalsePositives(int)">numFalsePositives</A></B>(int classIndex)</CODE><BR> Calculate number of false positives with respect to a particular class.</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/Evaluation.html#numInstances()">numInstances</A></B>()</CODE><BR> Gets the number of test instances that had a known class value (actually the sum of the weights of test instances with known class 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/Evaluation.html#numTrueNegatives(int)">numTrueNegatives</A></B>(int classIndex)</CODE><BR> Calculate the number of true negatives with respect to a particular class.</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/Evaluation.html#numTruePositives(int)">numTruePositives</A></B>(int classIndex)</CODE><BR> Calculate the number of true positives with respect to a particular class.</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/Evaluation.html#pctCorrect()">pctCorrect</A></B>()</CODE><BR> Gets the percentage of instances correctly classified (that is, for which a correct prediction was made).</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/Evaluation.html#pctIncorrect()">pctIncorrect</A></B>()</CODE><BR> Gets the percentage of instances incorrectly classified (that is, for which an incorrect prediction was made).</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/Evaluation.html#pctUnclassified()">pctUnclassified</A></B>()</CODE><BR> Gets the percentage of instances not classified (that is, for which no prediction was made by the classifier).</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor">⌨️ 快捷键说明
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