thresholdselector.html

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<DL>
<DD>Tooltip for this property.
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>

<DT><B>Returns:</B><DD>tip text for this property suitable for
                displaying in the explorer/experimenter gui</DL>
</DD>
</DL>
<HR>

<A NAME="setMeasure(weka.core.SelectedTag)"><!-- --></A><H3>
setMeasure</H3>
<PRE>
public void <B>setMeasure</B>(<A HREF="../../../weka/core/SelectedTag.html" title="class in weka.core">SelectedTag</A>&nbsp;newMeasure)</PRE>
<DL>
<DD>set measure used for determining threshold
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>newMeasure</CODE> - Tag representing measure to be used</DL>
</DD>
</DL>
<HR>

<A NAME="getMeasure()"><!-- --></A><H3>
getMeasure</H3>
<PRE>
public <A HREF="../../../weka/core/SelectedTag.html" title="class in weka.core">SelectedTag</A> <B>getMeasure</B>()</PRE>
<DL>
<DD>get measure used for determining threshold
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>

<DT><B>Returns:</B><DD>Tag representing measure used</DL>
</DD>
</DL>
<HR>

<A NAME="listOptions()"><!-- --></A><H3>
listOptions</H3>
<PRE>
public java.util.Enumeration <B>listOptions</B>()</PRE>
<DL>
<DD>Returns an enumeration describing the available options.
<P>
<DD><DL>
<DT><B>Specified by:</B><DD><CODE><A HREF="../../../weka/core/OptionHandler.html#listOptions()">listOptions</A></CODE> in interface <CODE><A HREF="../../../weka/core/OptionHandler.html" title="interface in weka.core">OptionHandler</A></CODE><DT><B>Overrides:</B><DD><CODE><A HREF="../../../weka/classifiers/RandomizableSingleClassifierEnhancer.html#listOptions()">listOptions</A></CODE> in class <CODE><A HREF="../../../weka/classifiers/RandomizableSingleClassifierEnhancer.html" title="class in weka.classifiers">RandomizableSingleClassifierEnhancer</A></CODE></DL>
</DD>
<DD><DL>

<DT><B>Returns:</B><DD>an enumeration of all the available options.</DL>
</DD>
</DL>
<HR>

<A NAME="setOptions(java.lang.String[])"><!-- --></A><H3>
setOptions</H3>
<PRE>
public void <B>setOptions</B>(java.lang.String[]&nbsp;options)
                throws java.lang.Exception</PRE>
<DL>
<DD>Parses a given list of options. <p/>

   <!-- options-start -->
 Valid options are: <p/>
 
 <pre> -C &lt;integer&gt;
  The class for which threshold is determined. Valid values are:
  1, 2 (for first and second classes, respectively), 3 (for whichever
  class is least frequent), and 4 (for whichever class value is most
  frequent), and 5 (for the first class named any of "yes","pos(itive)"
  "1", or method 3 if no matches). (default 5).</pre>
 
 <pre> -X &lt;number of folds&gt;
  Number of folds used for cross validation. If just a
  hold-out set is used, this determines the size of the hold-out set
  (default 3).</pre>
 
 <pre> -R &lt;integer&gt;
  Sets whether confidence range correction is applied. This
  can be used to ensure the confidences range from 0 to 1.
  Use 0 for no range correction, 1 for correction based on
  the min/max values seen during threshold selection
  (default 0).</pre>
 
 <pre> -E &lt;integer&gt;
  Sets the evaluation mode. Use 0 for
  evaluation using cross-validation,
  1 for evaluation using hold-out set,
  and 2 for evaluation on the
  training data (default 1).</pre>
 
 <pre> -M [FMEASURE|ACCURACY|TRUE_POS|TRUE_NEG|TP_RATE|PRECISION|RECALL]
  Measure used for evaluation (default is FMEASURE).
 </pre>
 
 <pre> -manual &lt;real&gt;
  Set a manual threshold to use. This option overrides
  automatic selection and options pertaining to
  automatic selection will be ignored.
  (default -1, i.e. do not use a manual threshold).</pre>
 
 <pre> -S &lt;num&gt;
  Random number seed.
  (default 1)</pre>
 
 <pre> -D
  If set, classifier is run in debug mode and
  may output additional info to the console</pre>
 
 <pre> -W
  Full name of base classifier.
  (default: weka.classifiers.functions.Logistic)</pre>
 
 <pre> 
 Options specific to classifier weka.classifiers.functions.Logistic:
 </pre>
 
 <pre> -D
  Turn on debugging output.</pre>
 
 <pre> -R &lt;ridge&gt;
  Set the ridge in the log-likelihood.</pre>
 
 <pre> -M &lt;number&gt;
  Set the maximum number of iterations (default -1, until convergence).</pre>
 
   <!-- options-end -->

 Options after -- are passed to the designated sub-classifier. <p>
<P>
<DD><DL>
<DT><B>Specified by:</B><DD><CODE><A HREF="../../../weka/core/OptionHandler.html#setOptions(java.lang.String[])">setOptions</A></CODE> in interface <CODE><A HREF="../../../weka/core/OptionHandler.html" title="interface in weka.core">OptionHandler</A></CODE><DT><B>Overrides:</B><DD><CODE><A HREF="../../../weka/classifiers/RandomizableSingleClassifierEnhancer.html#setOptions(java.lang.String[])">setOptions</A></CODE> in class <CODE><A HREF="../../../weka/classifiers/RandomizableSingleClassifierEnhancer.html" title="class in weka.classifiers">RandomizableSingleClassifierEnhancer</A></CODE></DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>options</CODE> - the list of options as an array of strings
<DT><B>Throws:</B>
<DD><CODE>java.lang.Exception</CODE> - if an option is not supported</DL>
</DD>
</DL>
<HR>

<A NAME="getOptions()"><!-- --></A><H3>
getOptions</H3>
<PRE>
public java.lang.String[] <B>getOptions</B>()</PRE>
<DL>
<DD>Gets the current settings of the Classifier.
<P>
<DD><DL>
<DT><B>Specified by:</B><DD><CODE><A HREF="../../../weka/core/OptionHandler.html#getOptions()">getOptions</A></CODE> in interface <CODE><A HREF="../../../weka/core/OptionHandler.html" title="interface in weka.core">OptionHandler</A></CODE><DT><B>Overrides:</B><DD><CODE><A HREF="../../../weka/classifiers/RandomizableSingleClassifierEnhancer.html#getOptions()">getOptions</A></CODE> in class <CODE><A HREF="../../../weka/classifiers/RandomizableSingleClassifierEnhancer.html" title="class in weka.classifiers">RandomizableSingleClassifierEnhancer</A></CODE></DL>
</DD>
<DD><DL>

<DT><B>Returns:</B><DD>an array of strings suitable for passing to setOptions</DL>
</DD>
</DL>
<HR>

<A NAME="getCapabilities()"><!-- --></A><H3>
getCapabilities</H3>
<PRE>
public <A HREF="../../../weka/core/Capabilities.html" title="class in weka.core">Capabilities</A> <B>getCapabilities</B>()</PRE>
<DL>
<DD>Returns default capabilities of the classifier.
<P>
<DD><DL>
<DT><B>Specified by:</B><DD><CODE><A HREF="../../../weka/core/CapabilitiesHandler.html#getCapabilities()">getCapabilities</A></CODE> in interface <CODE><A HREF="../../../weka/core/CapabilitiesHandler.html" title="interface in weka.core">CapabilitiesHandler</A></CODE><DT><B>Overrides:</B><DD><CODE><A HREF="../../../weka/classifiers/SingleClassifierEnhancer.html#getCapabilities()">getCapabilities</A></CODE> in class <CODE><A HREF="../../../weka/classifiers/SingleClassifierEnhancer.html" title="class in weka.classifiers">SingleClassifierEnhancer</A></CODE></DL>
</DD>
<DD><DL>

<DT><B>Returns:</B><DD>the capabilities of this classifier<DT><B>See Also:</B><DD><A HREF="../../../weka/core/Capabilities.html" title="class in weka.core"><CODE>Capabilities</CODE></A></DL>
</DD>
</DL>
<HR>

<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;instances)
                     throws java.lang.Exception</PRE>
<DL>
<DD>Generates the classifier.
<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>instances</CODE> - set of instances serving as 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="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>Calculates the class membership probabilities for the given test 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>predicted class probability distribution
<DT><B>Throws:</B>
<DD><CODE>java.lang.Exception</CODE> - if instance could not be classified
 successfully</DL>
</DD>
</DL>
<HR>

<A NAME="globalInfo()"><!-- --></A><H3>
globalInfo</H3>
<PRE>
public java.lang.String <B>globalInfo</B>()</PRE>
<DL>
<DD><DL>
</DL>
</DD>
<DD><DL>

<DT><B>Returns:</B><DD>a description of the classifier suitable for
 displaying in the explorer/experimenter gui</DL>
</DD>
</DL>
<HR>

<A NAME="designatedClassTipText()"><!-- --></A><H3>
designatedClassTipText</H3>
<PRE>
public java.lang.String <B>designatedClassTipText</B>()</PRE>
<DL>
<DD><DL>
</DL>
</DD>
<DD><DL>

<DT><B>Returns:</B><DD>tip text for this property suitable for
 displaying in the explorer/experimenter gui</DL>
</DD>
</DL>
<HR>

<A NAME="getDesignatedClass()"><!-- --></A><H3>
getDesignatedClass</H3>
<PRE>
public <A HREF="../../../weka/core/SelectedTag.html" title="class in weka.core">SelectedTag</A> <B>getDesignatedClass</B>()</PRE>
<DL>
<DD>Gets the method to determine which class value to optimize. Will
 be one of OPTIMIZE_0, OPTIMIZE_1, OPTIMIZE_LFREQ, OPTIMIZE_MFREQ,
 OPTIMIZE_POS_NAME.
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>

<DT><B>Returns:</B><DD>the class selection mode.</DL>
</DD>
</DL>
<HR>

<A NAME="setDesignatedClass(weka.core.SelectedTag)"><!-- --></A><H3>
setDesignatedClass</H3>
<PRE>
public void <B>setDesignatedClass</B>(<A HREF="../../../weka/core/SelectedTag.html" title="class in weka.core">SelectedTag</A>&nbsp;newMethod)</PRE>
<DL>
<DD>Sets the method to determine which class value to optimize. Will
 be one of OPTIMIZE_0, OPTIMIZE_1, OPTIMIZE_LFREQ, OPTIMIZE_MFREQ,
 OPTIMIZE_POS_NAME.
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>newMethod</CODE> - the new class selection mode.</DL>
</DD>
</DL>
<HR>

<A NAME="evaluationModeTipText()"><!-- --></A><H3>
evaluationModeTipText</H3>
<PRE>
public java.lang.String <B>evaluationModeTipText</B>()</PRE>
<DL>
<DD><DL>
</DL>
</DD>
<DD><DL>

<DT><B>Returns:</B><DD>tip text for this property suitable for
 displaying in the explorer/experimenter gui</DL>
</DD>
</DL>
<HR>

<A NAME="setEvaluationMode(weka.core.SelectedTag)"><!-- --></A><H3>
setEvaluationMode</H3>
<PRE>
public void <B>setEvaluationMode</B>(<A HREF="../../../weka/core/SelectedTag.html" title="class in weka.core">SelectedTag</A>&nbsp;newMethod)</PRE>
<DL>
<DD>Sets the evaluation mode used. Will be one of
 EVAL_TRAINING, EVAL_TUNED_SPLIT, or EVAL_CROSS_VALIDATION
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>newMethod</CODE> - the new evaluation mode.</DL>
</DD>
</DL>