📄 package-use.html
字号:
<TD><B><A HREF="../../../../com/rapidminer/operator/performance/class-use/PerformanceVector.html#com.rapidminer.operator.learner.functions"><B>PerformanceVector</B></A></B><BR> Handles several performance criteria.</TD></TR></TABLE> <P><A NAME="com.rapidminer.operator.learner.functions.kernel"><!-- --></A><TABLE BORDER="1" WIDTH="100%" CELLPADDING="3" CELLSPACING="0" SUMMARY=""><TR BGCOLOR="#CCCCFF" CLASS="TableHeadingColor"><TH ALIGN="left" COLSPAN="2"><FONT SIZE="+2">Classes in <A HREF="../../../../com/rapidminer/operator/performance/package-summary.html">com.rapidminer.operator.performance</A> used by <A HREF="../../../../com/rapidminer/operator/learner/functions/kernel/package-summary.html">com.rapidminer.operator.learner.functions.kernel</A></FONT></TH></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><B><A HREF="../../../../com/rapidminer/operator/performance/class-use/PerformanceVector.html#com.rapidminer.operator.learner.functions.kernel"><B>PerformanceVector</B></A></B><BR> Handles several performance criteria.</TD></TR></TABLE> <P><A NAME="com.rapidminer.operator.learner.functions.kernel.evosvm"><!-- --></A><TABLE BORDER="1" WIDTH="100%" CELLPADDING="3" CELLSPACING="0" SUMMARY=""><TR BGCOLOR="#CCCCFF" CLASS="TableHeadingColor"><TH ALIGN="left" COLSPAN="2"><FONT SIZE="+2">Classes in <A HREF="../../../../com/rapidminer/operator/performance/package-summary.html">com.rapidminer.operator.performance</A> used by <A HREF="../../../../com/rapidminer/operator/learner/functions/kernel/evosvm/package-summary.html">com.rapidminer.operator.learner.functions.kernel.evosvm</A></FONT></TH></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><B><A HREF="../../../../com/rapidminer/operator/performance/class-use/PerformanceVector.html#com.rapidminer.operator.learner.functions.kernel.evosvm"><B>PerformanceVector</B></A></B><BR> Handles several performance criteria.</TD></TR></TABLE> <P><A NAME="com.rapidminer.operator.learner.meta"><!-- --></A><TABLE BORDER="1" WIDTH="100%" CELLPADDING="3" CELLSPACING="0" SUMMARY=""><TR BGCOLOR="#CCCCFF" CLASS="TableHeadingColor"><TH ALIGN="left" COLSPAN="2"><FONT SIZE="+2">Classes in <A HREF="../../../../com/rapidminer/operator/performance/package-summary.html">com.rapidminer.operator.performance</A> used by <A HREF="../../../../com/rapidminer/operator/learner/meta/package-summary.html">com.rapidminer.operator.learner.meta</A></FONT></TH></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><B><A HREF="../../../../com/rapidminer/operator/performance/class-use/PerformanceVector.html#com.rapidminer.operator.learner.meta"><B>PerformanceVector</B></A></B><BR> Handles several performance criteria.</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">Classes in <A HREF="../../../../com/rapidminer/operator/performance/package-summary.html">com.rapidminer.operator.performance</A> used by <A HREF="../../../../com/rapidminer/operator/learner/weka/package-summary.html">com.rapidminer.operator.learner.weka</A></FONT></TH></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><B><A HREF="../../../../com/rapidminer/operator/performance/class-use/PerformanceVector.html#com.rapidminer.operator.learner.weka"><B>PerformanceVector</B></A></B><BR> Handles several performance criteria.</TD></TR></TABLE> <P><A NAME="com.rapidminer.operator.meta"><!-- --></A><TABLE BORDER="1" WIDTH="100%" CELLPADDING="3" CELLSPACING="0" SUMMARY=""><TR BGCOLOR="#CCCCFF" CLASS="TableHeadingColor"><TH ALIGN="left" COLSPAN="2"><FONT SIZE="+2">Classes in <A HREF="../../../../com/rapidminer/operator/performance/package-summary.html">com.rapidminer.operator.performance</A> used by <A HREF="../../../../com/rapidminer/operator/meta/package-summary.html">com.rapidminer.operator.meta</A></FONT></TH></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><B><A HREF="../../../../com/rapidminer/operator/performance/class-use/PerformanceVector.html#com.rapidminer.operator.meta"><B>PerformanceVector</B></A></B><BR> Handles several performance criteria.</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">Classes in <A HREF="../../../../com/rapidminer/operator/performance/package-summary.html">com.rapidminer.operator.performance</A> used by <A HREF="../../../../com/rapidminer/operator/performance/package-summary.html">com.rapidminer.operator.performance</A></FONT></TH></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><B><A HREF="../../../../com/rapidminer/operator/performance/class-use/AbsoluteError.html#com.rapidminer.operator.performance"><B>AbsoluteError</B></A></B><BR> The absolute error: <i>Sum(|label-predicted|)/#examples</i>.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><B><A HREF="../../../../com/rapidminer/operator/performance/class-use/AbstractPerformanceEvaluator.html#com.rapidminer.operator.performance"><B>AbstractPerformanceEvaluator</B></A></B><BR> This performance evaluator operator should be used for regression tasks, i.e. in cases where the label attribute has a numerical value type.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><B><A HREF="../../../../com/rapidminer/operator/performance/class-use/AreaUnderCurve.html#com.rapidminer.operator.performance"><B>AreaUnderCurve</B></A></B><BR> This criterion calculates the area under the ROC curve.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><B><A HREF="../../../../com/rapidminer/operator/performance/class-use/BinaryClassificationPerformance.html#com.rapidminer.operator.performance"><B>BinaryClassificationPerformance</B></A></B><BR> This class encapsulates the well known binary classification criteria precision and recall.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><B><A HREF="../../../../com/rapidminer/operator/performance/class-use/ClassWeightedPerformance.html#com.rapidminer.operator.performance"><B>ClassWeightedPerformance</B></A></B><BR> Performance criteria implementing this interface are able to calculate a performance measurement based on given class weights.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><B><A HREF="../../../../com/rapidminer/operator/performance/class-use/CorrelationCriterion.html#com.rapidminer.operator.performance"><B>CorrelationCriterion</B></A></B><BR> Computes the empirical corelation coefficient 'r' between label and prediction.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><B><A HREF="../../../../com/rapidminer/operator/performance/class-use/CrossEntropy.html#com.rapidminer.operator.performance"><B>CrossEntropy</B></A></B><BR> Calculates the cross-entropy for the predictions of a classifier.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><B><A HREF="../../../../com/rapidminer/operator/performance/class-use/EstimatedPerformance.html#com.rapidminer.operator.performance"><B>EstimatedPerformance</B></A></B><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><B><A HREF="../../../../com/rapidminer/operator/performance/class-use/LogisticLoss.html#com.rapidminer.operator.performance"><B>LogisticLoss</B></A></B><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><B><A HREF="../../../../com/rapidminer/operator/performance/class-use/Margin.html#com.rapidminer.operator.performance"><B>Margin</B></A></B><BR> The margin of a classifier, defined as the minimal confidence for the correct label.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><B><A HREF="../../../../com/rapidminer/operator/performance/class-use/MDLCriterion.html#com.rapidminer.operator.performance"><B>MDLCriterion</B></A></B><BR> Measures the length of an example set (i.e. the number of attributes).</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><B><A HREF="../../../../com/rapidminer/operator/performance/class-use/MeasuredPerformance.html#com.rapidminer.operator.performance"><B>MeasuredPerformance</B></A></B><BR> Superclass for performance citeria that are actually measured (not estimated).</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><B><A HREF="../../../../com/rapidminer/operator/performance/class-use/MinMaxCriterion.html#com.rapidminer.operator.performance"><B>MinMaxCriterion</B></A></B><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><B><A HREF="../../../../com/rapidminer/operator/performance/class-use/MultiClassificationPerformance.html#com.rapidminer.operator.performance"><B>MultiClassificationPerformance</B></A></B><BR> Measures the accuracy and classification error for both binary classification problems and multi class problems.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><B><A HREF="../../../../com/rapidminer/operator/performance/class-use/NormalizedAbsoluteError.html#com.rapidminer.operator.performance"><B>NormalizedAbsoluteError</B></A></B><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><B><A HREF="../../../../com/rapidminer/operator/performance/class-use/PerformanceComparator.html#com.rapidminer.operator.performance"><B>PerformanceComparator</B></A></B><BR> Compares two <A HREF="../../../../com/rapidminer/operator/performance/PerformanceVector.html" title="class in com.rapidminer.operator.performance"><CODE>PerformanceVector</CODE></A>s.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><B><A HREF="../../../../com/rapidminer/operator/performance/class-use/PerformanceCriterion.html#com.rapidminer.operator.performance"><B>PerformanceCriterion</B></A></B><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><B><A HREF="../../../../com/rapidminer/operator/performance/class-use/PerformanceVector.html#com.rapidminer.operator.performance"><B>PerformanceVector</B></A></B><BR> Handles several performance criteria.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><B><A HREF="../../../../com/rapidminer/operator/performance/class-use/PredictionAverage.html#com.rapidminer.operator.performance"><B>PredictionAverage</B></A></B><BR> Returns the average value of the prediction.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><B><A HREF="../../../../com/rapidminer/operator/performance/class-use/PredictionTrendAccuracy.html#com.rapidminer.operator.performance"><B>PredictionTrendAccuracy</B></A></B><BR> Measures the number of times a regression prediction correctly determines the trend.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><B><A HREF="../../../../com/rapidminer/operator/performance/class-use/RankCorrelation.html#com.rapidminer.operator.performance"><B>RankCorrelation</B></A></B><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">
⌨️ 快捷键说明
复制代码
Ctrl + C
搜索代码
Ctrl + F
全屏模式
F11
切换主题
Ctrl + Shift + D
显示快捷键
?
增大字号
Ctrl + =
减小字号
Ctrl + -