logisticbase.html

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<A NAME="LogisticBase()"><!-- --></A><H3>
LogisticBase</H3>
<PRE>
public <B>LogisticBase</B>()</PRE>
<DL>
<DD>Constructor that creates LogisticBase object with standard options.
<P>
</DL>
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<A NAME="LogisticBase(int, boolean, boolean)"><!-- --></A><H3>
LogisticBase</H3>
<PRE>
public <B>LogisticBase</B>(int&nbsp;numBoostingIterations,
                    boolean&nbsp;useCrossValidation,
                    boolean&nbsp;errorOnProbabilities)</PRE>
<DL>
<DD>Constructor to create LogisticBase object.
<P>
<DT><B>Parameters:</B><DD><CODE>numBoostingIterations</CODE> - fixed number of iterations for LogitBoost (if negative, use cross-validation or
 stopping criterion on the training data).<DD><CODE>useCrossValidation</CODE> - cross-validate number of LogitBoost iterations (if false, use stopping 
 criterion on the training data).<DD><CODE>errorOnProbabilities</CODE> - if true, use error on probabilities 
 instead of misclassification for stopping criterion of LogitBoost</DL>

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<A NAME="buildClassifier(weka.core.Instances)"><!-- --></A><H3>
buildClassifier</H3>
<PRE>
public void <B>buildClassifier</B>(<A HREF="../../../../weka/core/Instances.html" title="class in weka.core">Instances</A>&nbsp;data)
                     throws java.lang.Exception</PRE>
<DL>
<DD>Builds the logistic regression model usiing LogitBoost.
<P>
<DD><DL>
<DT><B>Specified by:</B><DD><CODE><A HREF="../../../../weka/classifiers/Classifier.html#buildClassifier(weka.core.Instances)">buildClassifier</A></CODE> in class <CODE><A HREF="../../../../weka/classifiers/Classifier.html" title="class in weka.classifiers">Classifier</A></CODE></DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>data</CODE> - the training data
<DT><B>Throws:</B>
<DD><CODE>java.lang.Exception</CODE> - if the classifier has not been 
 generated successfully</DL>
</DD>
</DL>
<HR>

<A NAME="getUsedAttributes()"><!-- --></A><H3>
getUsedAttributes</H3>
<PRE>
public int[][] <B>getUsedAttributes</B>()</PRE>
<DL>
<DD>Returns an array of the indices of the attributes used in the logistic model.
 The first dimension is the class, the second dimension holds a list of attribute indices.
 Attribute indices start at zero.
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>

<DT><B>Returns:</B><DD>the array of attribute indices</DL>
</DD>
</DL>
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<A NAME="getNumRegressions()"><!-- --></A><H3>
getNumRegressions</H3>
<PRE>
public int <B>getNumRegressions</B>()</PRE>
<DL>
<DD>The number of LogitBoost iterations performed (= the number of simple regression functions fit).
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>
</DL>
</DD>
</DL>
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<A NAME="setMaxIterations(int)"><!-- --></A><H3>
setMaxIterations</H3>
<PRE>
public void <B>setMaxIterations</B>(int&nbsp;maxIterations)</PRE>
<DL>
<DD>Sets the parameter "maxIterations".
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>
</DL>
</DD>
</DL>
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<A NAME="setHeuristicStop(int)"><!-- --></A><H3>
setHeuristicStop</H3>
<PRE>
public void <B>setHeuristicStop</B>(int&nbsp;heuristicStop)</PRE>
<DL>
<DD>Sets the option "heuristicStop".
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>
</DL>
</DD>
</DL>
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<A NAME="getMaxIterations()"><!-- --></A><H3>
getMaxIterations</H3>
<PRE>
public int <B>getMaxIterations</B>()</PRE>
<DL>
<DD>Returns the maxIterations parameter.
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>
</DL>
</DD>
</DL>
<HR>

<A NAME="percentAttributesUsed()"><!-- --></A><H3>
percentAttributesUsed</H3>
<PRE>
public double <B>percentAttributesUsed</B>()</PRE>
<DL>
<DD>Returns the fraction of all attributes in the data that are used in the logistic model (in percent).
 An attribute is used in the model if it is used in any of the models for the different classes.
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>
</DL>
</DD>
</DL>
<HR>

<A NAME="toString()"><!-- --></A><H3>
toString</H3>
<PRE>
public java.lang.String <B>toString</B>()</PRE>
<DL>
<DD>Returns a description of the logistic model (i.e., attributes and coefficients).
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>
</DL>
</DD>
</DL>
<HR>

<A NAME="distributionForInstance(weka.core.Instance)"><!-- --></A><H3>
distributionForInstance</H3>
<PRE>
public double[] <B>distributionForInstance</B>(<A HREF="../../../../weka/core/Instance.html" title="class in weka.core">Instance</A>&nbsp;instance)
                                 throws java.lang.Exception</PRE>
<DL>
<DD>Returns class probabilities for an instance.
<P>
<DD><DL>
<DT><B>Overrides:</B><DD><CODE><A HREF="../../../../weka/classifiers/Classifier.html#distributionForInstance(weka.core.Instance)">distributionForInstance</A></CODE> in class <CODE><A HREF="../../../../weka/classifiers/Classifier.html" title="class in weka.classifiers">Classifier</A></CODE></DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>instance</CODE> - the instance to be classified
<DT><B>Returns:</B><DD>an array containing the estimated membership 
 probabilities of the test instance in each class 
 or the numeric prediction
<DT><B>Throws:</B>
<DD><CODE>java.lang.Exception</CODE> - if distribution can't be computed successfully</DL>
</DD>
</DL>
<HR>

<A NAME="cleanup()"><!-- --></A><H3>
cleanup</H3>
<PRE>
public void <B>cleanup</B>()</PRE>
<DL>
<DD>Cleanup in order to save memory.
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>
</DL>
</DD>
</DL>
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