osdlcore.html

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<DD><DL>

<DT><B>Returns:</B><DD><code> true </code> if the balanced version is in effect,
 <code> false </code> otherwise</DL>
</DD>
</DL>
<HR>

<A NAME="weightedTipText()"><!-- --></A><H3>
weightedTipText</H3>
<PRE>
public java.lang.String <B>weightedTipText</B>()</PRE>
<DL>
<DD>Returns a string suitable for displaying in the gui/experimenter.
<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="setWeighted(boolean)"><!-- --></A><H3>
setWeighted</H3>
<PRE>
public void <B>setWeighted</B>(boolean&nbsp;weighted)</PRE>
<DL>
<DD>If <code> weighted </code> is <code> true </code> then the
 weighted version of the OSDL is used.
 Note: using the weighted (non-balanced) version only ensures the 
 quasi monotonicity of the results w.r.t. to training set.
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>weighted</CODE> - <code> true </code> if the weighted version to be used,
 <code> false </code> otherwise</DL>
</DD>
</DL>
<HR>

<A NAME="getWeighted()"><!-- --></A><H3>
getWeighted</H3>
<PRE>
public boolean <B>getWeighted</B>()</PRE>
<DL>
<DD>Returns if the weighted version is in effect.
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>

<DT><B>Returns:</B><DD><code> true </code> if the weighted version is in effect,
 <code> false </code> otherwise.</DL>
</DD>
</DL>
<HR>

<A NAME="getLowerBound()"><!-- --></A><H3>
getLowerBound</H3>
<PRE>
public double <B>getLowerBound</B>()</PRE>
<DL>
<DD>Returns the current value of the lower bound for the interpolation 
 parameter.
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>

<DT><B>Returns:</B><DD>the current value of the lower bound for the interpolation
 parameter</DL>
</DD>
</DL>
<HR>

<A NAME="getUpperBound()"><!-- --></A><H3>
getUpperBound</H3>
<PRE>
public double <B>getUpperBound</B>()</PRE>
<DL>
<DD>Returns the current value of the upper bound for the interpolation 
 parameter.
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>

<DT><B>Returns:</B><DD>the current value of the upper bound for the interpolation
 parameter</DL>
</DD>
</DL>
<HR>

<A NAME="getNumInstances()"><!-- --></A><H3>
getNumInstances</H3>
<PRE>
public int <B>getNumInstances</B>()</PRE>
<DL>
<DD>Returns the number of instances in the training set.
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>

<DT><B>Returns:</B><DD>the number of instances used for training</DL>
</DD>
</DL>
<HR>

<A NAME="tuneInterpolationParameter()"><!-- --></A><H3>
tuneInterpolationParameter</H3>
<PRE>
public double <B>tuneInterpolationParameter</B>()</PRE>
<DL>
<DD>Tune the interpolation parameter using the current
  settings of the classifier.
  This also sets the interpolation parameter.
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>

<DT><B>Returns:</B><DD>the value of the tuned interpolation parameter.</DL>
</DD>
</DL>
<HR>

<A NAME="tuneInterpolationParameter(double, double, int, int)"><!-- --></A><H3>
tuneInterpolationParameter</H3>
<PRE>
public double <B>tuneInterpolationParameter</B>(double&nbsp;sLow,
                                         double&nbsp;sUp,
                                         int&nbsp;sParts,
                                         int&nbsp;ctype)
                                  throws java.lang.IllegalArgumentException</PRE>
<DL>
<DD>Tunes the interpolation parameter using the given settings.
  The parameters of the classifier are updated accordingly!
  Marks the interpolation parameter as valid.
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>sLow</CODE> - lower end point of interval of paramters to be examined<DD><CODE>sUp</CODE> - upper end point of interval of paramters to be examined<DD><CODE>sParts</CODE> - number of parts the interval is divided into.  This thus determines
  the granularity of the search<DD><CODE>ctype</CODE> - the classification type to use
<DT><B>Returns:</B><DD>the value of the tuned interpolation parameter
<DT><B>Throws:</B>
<DD><CODE>java.lang.IllegalArgumentException</CODE> - if the given parameter list is not
  valid</DL>
</DD>
</DL>
<HR>

<A NAME="crossValidate()"><!-- --></A><H3>
crossValidate</H3>
<PRE>
public double <B>crossValidate</B>()
                     throws java.lang.IllegalArgumentException</PRE>
<DL>
<DD>Tunes the interpolation parameter using the current settings
  of the classifier.  This doesn't change the classifier, i.e.
  none of the internal parameters is changed!
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>

<DT><B>Returns:</B><DD>the tuned value of the interpolation parameter
<DT><B>Throws:</B>
<DD><CODE>java.lang.IllegalArgumentException</CODE> - if somehow the current settings of the 
  classifier are illegal.</DL>
</DD>
</DL>
<HR>

<A NAME="crossValidate(double, double, int, int)"><!-- --></A><H3>
crossValidate</H3>
<PRE>
public double <B>crossValidate</B>(double&nbsp;sLow,
                            double&nbsp;sUp,
                            int&nbsp;sNrParts,
                            int&nbsp;ctype)
                     throws java.lang.IllegalArgumentException</PRE>
<DL>
<DD>Tune the interpolation parameter using leave-one-out
  cross validation, the loss function used is the 1-0 loss
  function.
  <p>
  The given settings are used, but the classifier is not
  updated!.  Also, the interpolation parameter s is not 
  set.
  </p>
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>sLow</CODE> - lower end point of interval of paramters to be examined<DD><CODE>sUp</CODE> - upper end point of interval of paramters to be examined<DD><CODE>sNrParts</CODE> - number of parts the interval is divided into.  This thus determines
  the granularity of the search<DD><CODE>ctype</CODE> - the classification type to use
<DT><B>Returns:</B><DD>the best value for the interpolation parameter
<DT><B>Throws:</B>
<DD><CODE>java.lang.IllegalArgumentException</CODE> - if the settings for the
  interpolation parameter are not valid or if the classification 
  type is not valid</DL>
</DD>
</DL>
<HR>

<A NAME="crossValidate(double, double, int, int, double[], weka.classifiers.misc.monotone.NominalLossFunction)"><!-- --></A><H3>
crossValidate</H3>
<PRE>
public double <B>crossValidate</B>(double&nbsp;sLow,
                            double&nbsp;sUp,
                            int&nbsp;sNrParts,
                            int&nbsp;ctype,
                            double[]&nbsp;performanceStats,
                            <A HREF="../../../../weka/classifiers/misc/monotone/NominalLossFunction.html" title="interface in weka.classifiers.misc.monotone">NominalLossFunction</A>&nbsp;lossFunction)
                     throws java.lang.IllegalArgumentException</PRE>
<DL>
<DD>Tune the interpolation parameter using leave-one-out
 cross validation.  The given parameters are used, but 
 the classifier is not changed, in particular, the interpolation
 parameter remains unchanged.
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>sLow</CODE> - lower bound for interpolation parameter<DD><CODE>sUp</CODE> - upper bound for interpolation parameter<DD><CODE>sNrParts</CODE> - determines the granularity of the search<DD><CODE>ctype</CODE> - the classification type to use<DD><CODE>performanceStats</CODE> - array acting as output, and that will
 contain the total loss of the leave-one-out cross validation for
 each considered value of the interpolation parameter<DD><CODE>lossFunction</CODE> - the loss function to use
<DT><B>Returns:</B><DD>the value of the interpolation parameter that is considered
 best
<DT><B>Throws:</B>
<DD><CODE>java.lang.IllegalArgumentException</CODE> - the length of the array 
 <code> performanceStats </code> is not sufficient
<DD><CODE>java.lang.IllegalArgumentException</CODE> - if the interpolation parameters 
 are not valid
<DD><CODE>java.lang.IllegalArgumentException</CODE> - if the classification type is 
 not valid</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.
 For a list of available options, see <code> setOptions </code>.
<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/Classifier.html#listOptions()">listOptions</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>Returns:</B><DD>an enumeration of all 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 the options for this object. <p/>

   <!-- options-start -->
 Valid options are: <p/>
 
 <pre> -D
  If set, classifier is run in debug mode and
  may output additional info to the console</pre>
 
 <pre> -C &lt;REG|WSUM|MAX|MED|RMED&gt;
  Sets the classification type to be used.
  (Default: MED)</pre>
 
 <pre> -B
  Use the balanced version of the Ordinal Stochastic Dominance Learner</pre>
 
 <pre> -W
  Use the weighted version of the Ordinal Stochastic Dominance Learner</pre>
 
 <pre> -S &lt;value of interpolation parameter&gt;
  Sets the value of the interpolation parameter (not with -W/T/P/L/U)
  (default: 0.5).</pre>
 
 <pre> -T
  Tune the interpolation parameter (not with -W/S)
  (default: off)</pre>
 
 <pre> -L &lt;Lower bound for interpolation parameter&gt;
  Lower bound for the interpolation parameter (not with -W/S)
  (default: 0)</pre>
 
 <pre> -U &lt;Upper bound for interpolation parameter&gt;
  Upper bound for the interpolation parameter (not with -W/S)
  (default: 1)</pre>
 
 <pre> -P &lt;Number of parts&gt;
  Determines the step size for tuning the interpolation
  parameter, nl. (U-L)/P (not with -W/S)
  (default: 10)</pre>
 
   <!-- options-end -->
<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/Classifier.html#setOptions(java.lang.String[])">setOptions</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>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