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<TR BGCOLOR="#CCCCFF" CLASS="TableHeadingColor"><TH ALIGN="left" COLSPAN="2"><FONT SIZE="+2">Uses of <A HREF="../../../../com/rapidminer/report/Readable.html" title="interface in com.rapidminer.report">Readable</A> in <A HREF="../../../../com/rapidminer/operator/learner/tree/package-summary.html">com.rapidminer.operator.learner.tree</A></FONT></TH></TR></TABLE> <P><TABLE BORDER="1" WIDTH="100%" CELLPADDING="3" CELLSPACING="0" SUMMARY=""><TR BGCOLOR="#CCCCFF" CLASS="TableSubHeadingColor"><TH ALIGN="left" COLSPAN="2">Classes in <A HREF="../../../../com/rapidminer/operator/learner/tree/package-summary.html">com.rapidminer.operator.learner.tree</A> that implement <A HREF="../../../../com/rapidminer/report/Readable.html" title="interface in com.rapidminer.report">Readable</A></FONT></TH></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>static class</CODE></FONT></TD><TD><CODE><B><A HREF="../../../../com/rapidminer/operator/learner/tree/MultiCriterionDecisionStumps.DecisionStumpModel.html" title="class in com.rapidminer.operator.learner.tree">MultiCriterionDecisionStumps.DecisionStumpModel</A></B></CODE><BR> </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> class</CODE></FONT></TD><TD><CODE><B><A HREF="../../../../com/rapidminer/operator/learner/tree/TreeModel.html" title="class in com.rapidminer.operator.learner.tree">TreeModel</A></B></CODE><BR> The tree model is the model created by all decision trees.</TD></TR></TABLE> <P><A NAME="com.rapidminer.operator.learner.weka"><!-- --></A><TABLE BORDER="1" WIDTH="100%" CELLPADDING="3" CELLSPACING="0" SUMMARY=""><TR BGCOLOR="#CCCCFF" CLASS="TableHeadingColor"><TH ALIGN="left" COLSPAN="2"><FONT SIZE="+2">Uses of <A HREF="../../../../com/rapidminer/report/Readable.html" title="interface in com.rapidminer.report">Readable</A> in <A HREF="../../../../com/rapidminer/operator/learner/weka/package-summary.html">com.rapidminer.operator.learner.weka</A></FONT></TH></TR></TABLE> <P><TABLE BORDER="1" WIDTH="100%" CELLPADDING="3" CELLSPACING="0" SUMMARY=""><TR BGCOLOR="#CCCCFF" CLASS="TableSubHeadingColor"><TH ALIGN="left" COLSPAN="2">Classes in <A HREF="../../../../com/rapidminer/operator/learner/weka/package-summary.html">com.rapidminer.operator.learner.weka</A> that implement <A HREF="../../../../com/rapidminer/report/Readable.html" title="interface in com.rapidminer.report">Readable</A></FONT></TH></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> class</CODE></FONT></TD><TD><CODE><B><A HREF="../../../../com/rapidminer/operator/learner/weka/WekaClassifier.html" title="class in com.rapidminer.operator.learner.weka">WekaClassifier</A></B></CODE><BR> A Weka <CODE>Classifier</CODE> which can be used to classify <A HREF="../../../../com/rapidminer/example/Example.html" title="class in com.rapidminer.example"><CODE>Example</CODE></A>s.</TD></TR></TABLE> <P><A NAME="com.rapidminer.operator.performance"><!-- --></A><TABLE BORDER="1" WIDTH="100%" CELLPADDING="3" CELLSPACING="0" SUMMARY=""><TR BGCOLOR="#CCCCFF" CLASS="TableHeadingColor"><TH ALIGN="left" COLSPAN="2"><FONT SIZE="+2">Uses of <A HREF="../../../../com/rapidminer/report/Readable.html" title="interface in com.rapidminer.report">Readable</A> in <A HREF="../../../../com/rapidminer/operator/performance/package-summary.html">com.rapidminer.operator.performance</A></FONT></TH></TR></TABLE> <P><TABLE BORDER="1" WIDTH="100%" CELLPADDING="3" CELLSPACING="0" SUMMARY=""><TR BGCOLOR="#CCCCFF" CLASS="TableSubHeadingColor"><TH ALIGN="left" COLSPAN="2">Classes in <A HREF="../../../../com/rapidminer/operator/performance/package-summary.html">com.rapidminer.operator.performance</A> that implement <A HREF="../../../../com/rapidminer/report/Readable.html" title="interface in com.rapidminer.report">Readable</A></FONT></TH></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> class</CODE></FONT></TD><TD><CODE><B><A HREF="../../../../com/rapidminer/operator/performance/AbsoluteError.html" title="class in com.rapidminer.operator.performance">AbsoluteError</A></B></CODE><BR> The absolute error: <i>Sum(|label-predicted|)/#examples</i>.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> class</CODE></FONT></TD><TD><CODE><B><A HREF="../../../../com/rapidminer/operator/performance/AreaUnderCurve.html" title="class in com.rapidminer.operator.performance">AreaUnderCurve</A></B></CODE><BR> This criterion calculates the area under the ROC curve.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> class</CODE></FONT></TD><TD><CODE><B><A HREF="../../../../com/rapidminer/operator/performance/BinaryClassificationPerformance.html" title="class in com.rapidminer.operator.performance">BinaryClassificationPerformance</A></B></CODE><BR> This class encapsulates the well known binary classification criteria precision and recall.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> class</CODE></FONT></TD><TD><CODE><B><A HREF="../../../../com/rapidminer/operator/performance/CorrelationCriterion.html" title="class in com.rapidminer.operator.performance">CorrelationCriterion</A></B></CODE><BR> Computes the empirical corelation coefficient 'r' between label and prediction.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> class</CODE></FONT></TD><TD><CODE><B><A HREF="../../../../com/rapidminer/operator/performance/CrossEntropy.html" title="class in com.rapidminer.operator.performance">CrossEntropy</A></B></CODE><BR> Calculates the cross-entropy for the predictions of a classifier.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> class</CODE></FONT></TD><TD><CODE><B><A HREF="../../../../com/rapidminer/operator/performance/EstimatedPerformance.html" title="class in com.rapidminer.operator.performance">EstimatedPerformance</A></B></CODE><BR> This class is used to store estimated performance values <em>before</em> or even <em>without</em> the performance test is actually done using a test set.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> class</CODE></FONT></TD><TD><CODE><B><A HREF="../../../../com/rapidminer/operator/performance/LogisticLoss.html" title="class in com.rapidminer.operator.performance">LogisticLoss</A></B></CODE><BR> The logistic loss of a classifier, defined as the average over all ln(1 + exp(-y * f(x)))</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> class</CODE></FONT></TD><TD><CODE><B><A HREF="../../../../com/rapidminer/operator/performance/Margin.html" title="class in com.rapidminer.operator.performance">Margin</A></B></CODE><BR> The margin of a classifier, defined as the minimal confidence for the correct label.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> class</CODE></FONT></TD><TD><CODE><B><A HREF="../../../../com/rapidminer/operator/performance/MDLCriterion.html" title="class in com.rapidminer.operator.performance">MDLCriterion</A></B></CODE><BR> Measures the length of an example set (i.e. the number of attributes).</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> class</CODE></FONT></TD><TD><CODE><B><A HREF="../../../../com/rapidminer/operator/performance/MeasuredPerformance.html" title="class in com.rapidminer.operator.performance">MeasuredPerformance</A></B></CODE><BR> Superclass for performance citeria that are actually measured (not estimated).</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> class</CODE></FONT></TD><TD><CODE><B><A HREF="../../../../com/rapidminer/operator/performance/MinMaxCriterion.html" title="class in com.rapidminer.operator.performance">MinMaxCriterion</A></B></CODE><BR> This criterion should be used as wrapper around other performance criteria (see <A HREF="../../../../com/rapidminer/operator/performance/MinMaxWrapper.html" title="class in com.rapidminer.operator.performance"><CODE>MinMaxWrapper</CODE></A>).</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> class</CODE></FONT></TD><TD><CODE><B><A HREF="../../../../com/rapidminer/operator/performance/MultiClassificationPerformance.html" title="class in com.rapidminer.operator.performance">MultiClassificationPerformance</A></B></CODE><BR> Measures the accuracy and classification error for both binary classification problems and multi class problems.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> class</CODE></FONT></TD><TD><CODE><B><A HREF="../../../../com/rapidminer/operator/performance/NormalizedAbsoluteError.html" title="class in com.rapidminer.operator.performance">NormalizedAbsoluteError</A></B></CODE><BR> Normalized absolute error is the total absolute error normalized by the error simply predicting the average of the actual values.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> class</CODE></FONT></TD><TD><CODE><B><A HREF="../../../../com/rapidminer/operator/performance/PerformanceCriterion.html" title="class in com.rapidminer.operator.performance">PerformanceCriterion</A></B></CODE><BR> Each <tt>PerformanceCriterion</tt> contains a method to compute this criterion on a given set of examples, each which has to have a real and a predicted label.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> class</CODE></FONT></TD><TD><CODE><B><A HREF="../../../../com/rapidminer/operator/performance/PredictionAverage.html" title="class in com.rapidminer.operator.performance">PredictionAverage</A></B></CODE><BR> Returns the average value of the prediction.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> class</CODE></FONT></TD><TD><CODE><B><A HREF="../../../../com/rapidminer/operator/performance/PredictionTrendAccuracy.html" title="class in com.rapidminer.operator.performance">PredictionTrendAccuracy</A></B></CODE><BR> Measures the number of times a regression prediction correctly determines the trend.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> class</CODE></FONT></TD><TD><CODE><B><A HREF="../../../../com/rapidminer/operator/performance/RankCorrelation.html" title="class in com.rapidminer.operator.performance">RankCorrelation</A></B></CODE><BR> Computes either the Spearman (rho) or Kendall (tau-b) rank correlation between the actual label and predicted values of an example set.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> class</CODE></FONT></TD><TD><CODE><B><A HREF="../../../../com/rapidminer/operator/performance/RelativeError.html" title="class in com.rapidminer.operator.performance">RelativeError</A></B></CODE><BR> The average relative error: <i>Sum(|label-predicted|/label)/#examples</i>.</TD></TR><T⌨️ 快捷键说明
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