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</DL></DD><DD><DL><DT><B>Returns:</B><DD>the K&B information score<DT><B>Throws:</B><DD><CODE>java.lang.Exception</CODE> - if the class is not nominal</DL></DD></DL><HR><A NAME="KBRelativeInformation()"><!-- --></A><H3>KBRelativeInformation</H3><PRE>public final double <B>KBRelativeInformation</B>()                                   throws java.lang.Exception</PRE><DL><DD>Return the Kononenko & Bratko Relative Information score<P><DD><DL></DL></DD><DD><DL><DT><B>Returns:</B><DD>the K&B relative information score<DT><B>Throws:</B><DD><CODE>java.lang.Exception</CODE> - if the class is not nominal</DL></DD></DL><HR><A NAME="SFPriorEntropy()"><!-- --></A><H3>SFPriorEntropy</H3><PRE>public final double <B>SFPriorEntropy</B>()</PRE><DL><DD>Returns the total entropy for the null model<P><DD><DL></DL></DD><DD><DL><DT><B>Returns:</B><DD>the total null model entropy</DL></DD></DL><HR><A NAME="SFMeanPriorEntropy()"><!-- --></A><H3>SFMeanPriorEntropy</H3><PRE>public final double <B>SFMeanPriorEntropy</B>()</PRE><DL><DD>Returns the entropy per instance for the null model<P><DD><DL></DL></DD><DD><DL><DT><B>Returns:</B><DD>the null model entropy per instance</DL></DD></DL><HR><A NAME="SFSchemeEntropy()"><!-- --></A><H3>SFSchemeEntropy</H3><PRE>public final double <B>SFSchemeEntropy</B>()</PRE><DL><DD>Returns the total entropy for the scheme<P><DD><DL></DL></DD><DD><DL><DT><B>Returns:</B><DD>the total scheme entropy</DL></DD></DL><HR><A NAME="SFMeanSchemeEntropy()"><!-- --></A><H3>SFMeanSchemeEntropy</H3><PRE>public final double <B>SFMeanSchemeEntropy</B>()</PRE><DL><DD>Returns the entropy per instance for the scheme<P><DD><DL></DL></DD><DD><DL><DT><B>Returns:</B><DD>the scheme entropy per instance</DL></DD></DL><HR><A NAME="SFEntropyGain()"><!-- --></A><H3>SFEntropyGain</H3><PRE>public final double <B>SFEntropyGain</B>()</PRE><DL><DD>Returns the total SF, which is the null model entropy minus the scheme entropy.<P><DD><DL></DL></DD><DD><DL><DT><B>Returns:</B><DD>the total SF</DL></DD></DL><HR><A NAME="SFMeanEntropyGain()"><!-- --></A><H3>SFMeanEntropyGain</H3><PRE>public final double <B>SFMeanEntropyGain</B>()</PRE><DL><DD>Returns the SF per instance, which is the null model entropy minus the scheme entropy, per instance.<P><DD><DL></DL></DD><DD><DL><DT><B>Returns:</B><DD>the SF per instance</DL></DD></DL><HR><A NAME="toCumulativeMarginDistributionString()"><!-- --></A><H3>toCumulativeMarginDistributionString</H3><PRE>public java.lang.String <B>toCumulativeMarginDistributionString</B>()                                                      throws java.lang.Exception</PRE><DL><DD>Output the cumulative margin distribution as a string suitable for input for gnuplot or similar package.<P><DD><DL></DL></DD><DD><DL><DT><B>Returns:</B><DD>the cumulative margin distribution<DT><B>Throws:</B><DD><CODE>java.lang.Exception</CODE> - if the class attribute is nominal</DL></DD></DL><HR><A NAME="toSummaryString()"><!-- --></A><H3>toSummaryString</H3><PRE>public java.lang.String <B>toSummaryString</B>()</PRE><DL><DD>Calls toSummaryString() with no title and no complexity stats<P><DD><DL><DT><B>Specified by:</B><DD><CODE><A HREF="../../weka/core/Summarizable.html#toSummaryString()">toSummaryString</A></CODE> in interface <CODE><A HREF="../../weka/core/Summarizable.html" title="interface in weka.core">Summarizable</A></CODE></DL></DD><DD><DL><DT><B>Returns:</B><DD>a summary description of the classifier evaluation</DL></DD></DL><HR><A NAME="toSummaryString(boolean)"><!-- --></A><H3>toSummaryString</H3><PRE>public java.lang.String <B>toSummaryString</B>(boolean&nbsp;printComplexityStatistics)</PRE><DL><DD>Calls toSummaryString() with a default title.<P><DD><DL></DL></DD><DD><DL><DT><B>Parameters:</B><DD><CODE>printComplexityStatistics</CODE> - if true, complexity statistics are returned as well</DL></DD></DL><HR><A NAME="toSummaryString(java.lang.String, boolean)"><!-- --></A><H3>toSummaryString</H3><PRE>public java.lang.String <B>toSummaryString</B>(java.lang.String&nbsp;title,                                        boolean&nbsp;printComplexityStatistics)</PRE><DL><DD>Outputs the performance statistics in summary form. Lists  number (and percentage) of instances classified correctly,  incorrectly and unclassified. Outputs the total number of  instances classified, and the number of instances (if any)  that had no class value provided.<P><DD><DL></DL></DD><DD><DL><DT><B>Parameters:</B><DD><CODE>title</CODE> - the title for the statistics<DD><CODE>printComplexityStatistics</CODE> - if true, complexity statistics are returned as well<DT><B>Returns:</B><DD>the summary as a String</DL></DD></DL><HR><A NAME="toMatrixString()"><!-- --></A><H3>toMatrixString</H3><PRE>public java.lang.String <B>toMatrixString</B>()                                throws java.lang.Exception</PRE><DL><DD>Calls toMatrixString() with a default title.<P><DD><DL></DL></DD><DD><DL><DT><B>Returns:</B><DD>the confusion matrix as a string<DT><B>Throws:</B><DD><CODE>java.lang.Exception</CODE> - if the class is numeric</DL></DD></DL><HR><A NAME="toMatrixString(java.lang.String)"><!-- --></A><H3>toMatrixString</H3><PRE>public java.lang.String <B>toMatrixString</B>(java.lang.String&nbsp;title)                                throws java.lang.Exception</PRE><DL><DD>Outputs the performance statistics as a classification confusion matrix. For each class value, shows the distribution of  predicted class values.<P><DD><DL></DL></DD><DD><DL><DT><B>Parameters:</B><DD><CODE>title</CODE> - the title for the confusion matrix<DT><B>Returns:</B><DD>the confusion matrix as a String<DT><B>Throws:</B><DD><CODE>java.lang.Exception</CODE> - if the class is numeric</DL></DD></DL><HR><A NAME="toClassDetailsString()"><!-- --></A><H3>toClassDetailsString</H3><PRE>public java.lang.String <B>toClassDetailsString</B>()                                      throws java.lang.Exception</PRE><DL><DD><DL></DL></DD><DD><DL><DT><B>Throws:</B><DD><CODE>java.lang.Exception</CODE></DL></DD></DL><HR><A NAME="toClassDetailsString(java.lang.String)"><!-- --></A><H3>toClassDetailsString</H3><PRE>public java.lang.String <B>toClassDetailsString</B>(java.lang.String&nbsp;title)                                      throws java.lang.Exception</PRE><DL><DD>Generates a breakdown of the accuracy for each class, incorporating various information-retrieval statistics, such as true/false positive rate, precision/recall/F-Measure.  Should be useful for ROC curves, recall/precision curves.<P><DD><DL></DL></DD><DD><DL><DT><B>Parameters:</B><DD><CODE>title</CODE> - the title to prepend the stats string with<DT><B>Returns:</B><DD>the statistics presented as a string<DT><B>Throws:</B><DD><CODE>java.lang.Exception</CODE></DL></DD></DL><HR><A NAME="numTruePositives(int)"><!-- --></A><H3>numTruePositives</H3><PRE>public double <B>numTruePositives</B>(int&nbsp;classIndex)</PRE><DL><DD>Calculate the number of true positives with respect to a particular class.  This is defined as<p> <pre> correctly classified positives </pre><P><DD><DL></DL></DD><DD><DL><DT><B>Parameters:</B><DD><CODE>classIndex</CODE> - the index of the class to consider as "positive"<DT><B>Returns:</B><DD>the true positive rate</DL></DD></DL><HR><A NAME="truePositiveRate(int)"><!-- --></A><H3>truePositiveRate</H3><PRE>public double <B>truePositiveRate</B>(int&nbsp;classIndex)</PRE><DL><DD>Calculate the true positive rate with respect to a particular class.  This is defined as<p> <pre> correctly classified positives ------------------------------       total positives </pre><P><DD><DL></DL></DD><DD><DL><DT><B>Parameters:</B><DD><CODE>classIndex</CODE> - the index of the class to consider as "positive"<DT><B>Returns:</B><DD>the true positive rate</DL></DD></DL><HR><A NAME="numTrueNegatives(int)"><!-- --></A><H3>numTrueNegatives</H3><PRE>public double <B>numTrueNegatives</B>(int&nbsp;classIndex)</PRE><DL><DD>Calculate the number of true negatives with respect to a particular class.  This is defined as<p> <pre> correctly classified negatives </pre><P><DD><DL></DL></DD><DD><DL><DT><B>Parameters:</B><DD><CODE>classIndex</CODE> - the index of the class to consider as "positive"<DT><B>Returns:</B><DD>the true positive rate</DL></DD></DL><HR><A NAME="trueNegativeRate(int)"><!-- --></A><H3>trueNegativeRate</H3><PRE>public double <B>trueNegativeRate</B>(int&nbsp;classIndex)</PRE><DL><DD>Calculate the true negative rate with respect to a particular class.  This is defined as<p> <pre> correctly classified negatives ------------------------------       total negatives </pre><P><DD><DL></DL></DD><DD><DL><DT><B>Parameters:</B><DD><CODE>classIndex</CODE> - the index of the class to consider as "positive"<DT><B>Returns:</B><DD>the true positive rate<

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