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<TH ALIGN="left"><B>Methods inherited from class java.lang.Object</B></TH></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><CODE>equals, getClass, hashCode, notify, notifyAll, wait, wait, wait</CODE></TD></TR></TABLE> <P><!-- ============ FIELD DETAIL =========== --><A NAME="field_detail"><!-- --></A><TABLE BORDER="1" WIDTH="100%" CELLPADDING="3" CELLSPACING="0" SUMMARY=""><TR BGCOLOR="#CCCCFF" CLASS="TableHeadingColor"><TH ALIGN="left" COLSPAN="1"><FONT SIZE="+2"><B>Field Detail</B></FONT></TH></TR></TABLE><A NAME="CT_REGRESSION"><!-- --></A><H3>CT_REGRESSION</H3><PRE>public static final int <B>CT_REGRESSION</B></PRE><DL><DD>Constant indicating that the classification type is regression (probabilistic weighted sum).<P><DL><DT><B>See Also:</B><DD><A HREF="../../../../constant-values.html#weka.classifiers.misc.monotone.OSDLCore.CT_REGRESSION">Constant Field Values</A></DL></DL><HR><A NAME="CT_WEIGHTED_SUM"><!-- --></A><H3>CT_WEIGHTED_SUM</H3><PRE>public static final int <B>CT_WEIGHTED_SUM</B></PRE><DL><DD>Constant indicating that the classification type is the probabilistic weighted sum.<P><DL><DT><B>See Also:</B><DD><A HREF="../../../../constant-values.html#weka.classifiers.misc.monotone.OSDLCore.CT_WEIGHTED_SUM">Constant Field Values</A></DL></DL><HR><A NAME="CT_MAXPROB"><!-- --></A><H3>CT_MAXPROB</H3><PRE>public static final int <B>CT_MAXPROB</B></PRE><DL><DD>Constant indicating that the classification type is the mode of the distribution.<P><DL><DT><B>See Also:</B><DD><A HREF="../../../../constant-values.html#weka.classifiers.misc.monotone.OSDLCore.CT_MAXPROB">Constant Field Values</A></DL></DL><HR><A NAME="CT_MEDIAN"><!-- --></A><H3>CT_MEDIAN</H3><PRE>public static final int <B>CT_MEDIAN</B></PRE><DL><DD>Constant indicating that the classification type is the median.<P><DL><DT><B>See Also:</B><DD><A HREF="../../../../constant-values.html#weka.classifiers.misc.monotone.OSDLCore.CT_MEDIAN">Constant Field Values</A></DL></DL><HR><A NAME="CT_MEDIAN_REAL"><!-- --></A><H3>CT_MEDIAN_REAL</H3><PRE>public static final int <B>CT_MEDIAN_REAL</B></PRE><DL><DD>Constant indicating that the classification type is the median, but not rounded to the nearest class.<P><DL><DT><B>See Also:</B><DD><A HREF="../../../../constant-values.html#weka.classifiers.misc.monotone.OSDLCore.CT_MEDIAN_REAL">Constant Field Values</A></DL></DL><HR><A NAME="TAGS_CLASSIFICATIONTYPES"><!-- --></A><H3>TAGS_CLASSIFICATIONTYPES</H3><PRE>public static final <A HREF="../../../../weka/core/Tag.html" title="class in weka.core">Tag</A>[] <B>TAGS_CLASSIFICATIONTYPES</B></PRE><DL><DD>the classification types<P><DL></DL></DL><!-- ========= CONSTRUCTOR DETAIL ======== --><A NAME="constructor_detail"><!-- --></A><TABLE BORDER="1" WIDTH="100%" CELLPADDING="3" CELLSPACING="0" SUMMARY=""><TR BGCOLOR="#CCCCFF" CLASS="TableHeadingColor"><TH ALIGN="left" COLSPAN="1"><FONT SIZE="+2"><B>Constructor Detail</B></FONT></TH></TR></TABLE><A NAME="OSDLCore()"><!-- --></A><H3>OSDLCore</H3><PRE>public <B>OSDLCore</B>()</PRE><DL></DL><!-- ============ METHOD DETAIL ========== --><A NAME="method_detail"><!-- --></A><TABLE BORDER="1" WIDTH="100%" CELLPADDING="3" CELLSPACING="0" SUMMARY=""><TR BGCOLOR="#CCCCFF" CLASS="TableHeadingColor"><TH ALIGN="left" COLSPAN="1"><FONT SIZE="+2"><B>Method Detail</B></FONT></TH></TR></TABLE><A NAME="globalInfo()"><!-- --></A><H3>globalInfo</H3><PRE>public java.lang.String <B>globalInfo</B>()</PRE><DL><DD>Returns a string describing the classifier.<P><DD><DL></DL></DD><DD><DL><DT><B>Returns:</B><DD>a description suitable for displaying in the explorer/experimenter gui</DL></DD></DL><HR><A NAME="getTechnicalInformation()"><!-- --></A><H3>getTechnicalInformation</H3><PRE>public <A HREF="../../../../weka/core/TechnicalInformation.html" title="class in weka.core">TechnicalInformation</A> <B>getTechnicalInformation</B>()</PRE><DL><DD>Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.<P><DD><DL><DT><B>Specified by:</B><DD><CODE><A HREF="../../../../weka/core/TechnicalInformationHandler.html#getTechnicalInformation()">getTechnicalInformation</A></CODE> in interface <CODE><A HREF="../../../../weka/core/TechnicalInformationHandler.html" title="interface in weka.core">TechnicalInformationHandler</A></CODE></DL></DD><DD><DL><DT><B>Returns:</B><DD>the technical information about this class</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/Classifier.html#getCapabilities()">getCapabilities</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>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="classifyInstance(weka.core.Instance)"><!-- --></A><H3>classifyInstance</H3><PRE>public double <B>classifyInstance</B>(<A HREF="../../../../weka/core/Instance.html" title="class in weka.core">Instance</A> instance) throws java.lang.Exception</PRE><DL><DD>Classifies a given instance using the current settings of the classifier.<P><DD><DL><DT><B>Overrides:</B><DD><CODE><A HREF="../../../../weka/classifiers/Classifier.html#classifyInstance(weka.core.Instance)">classifyInstance</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>the classification for the instance. Depending on the settings of the classifier this is a double representing a classlabel (internal WEKA format) or a real value in the sense of regression.<DT><B>Throws:</B><DD><CODE>java.lang.Exception</CODE> - if for some reason no distribution could be predicted</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> instance)</PRE><DL><DD>Calculates the class probabilities for the given test instance. Uses the current settings of the parameters if these are valid. If necessary it updates the interpolationparameter first, and hence this may change the classifier.<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 of doubles representing the predicted probability distribution over the class labels</DL></DD></DL><HR><A NAME="cumulativeDistributionForInstance(weka.core.Instance)"><!-- --></A><H3>cumulativeDistributionForInstance</H3><PRE>public double[] <B>cumulativeDistributionForInstance</B>(<A HREF="../../../../weka/core/Instance.html" title="class in weka.core">Instance</A> instance)</PRE><DL><DD>Calculates the cumulative class probabilities for the given test instance. Uses the current settings of the parameters if these are valid. If necessary it updates the interpolationparameter first, and hence this may change the classifier.<P><DD><DL></DL></DD><DD><DL><DT><B>Parameters:</B><DD><CODE>instance</CODE> - the instance to be classified<DT><B>Returns:</B><DD>an array of doubles representing the predicted cumulative probability distribution over the class labels</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> instances) throws java.lang.Exception</PRE><DL><DD>Builds the classifier. This means that all relevant examples are stored into memory. If necessary the interpolation parameter is tuned.<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> - the instances to be used for building the classifier<DT><B>Throws:</B><DD><CODE>java.lang.Exception</CODE> - if the classifier can't be built successfully</DL></DD></DL><HR><A NAME="classificationTypeTipText()"><!-- --></A><H3>classificationTypeTipText</H3><PRE>public java.lang.String <B>classificationTypeTipText</B>()</PRE><DL><DD>Returns the tip text 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="setClassificationType(weka.core.SelectedTag)"><!-- --></A><H3>setClassificationType</H3><PRE>public void <B>setClassificationType</B>(<A HREF="../../../../weka/core/SelectedTag.html" title="class in weka.core">SelectedTag</A> value)</PRE><DL><DD>Sets the classification type. Currently <code> ctype </code> must be one of: <ul> <li> <code> CT_REGRESSION </code> : use expectation value of distribution. (Non-ordinal in nature). <li> <code> CT_WEIGHTED_SUM </code> : use expectation value of distribution rounded to nearest class label. (Non-ordinal in nature). <li> <code> CT_MAXPROB </code> : use the mode of the distribution. (May deliver non-monotone results). <li> <code> CT_MEDIAN </code> : use the median of the distribution (rounded to the nearest class label). <li> <code> CT_MEDIAN_REAL </code> : use the median of the distribution but not rounded to the nearest class label. </ul><P><DD><DL></DL></DD><DD><DL><DT><B>Parameters:</B><DD><CODE>value</CODE> - the classification type</DL></DD></DL><HR><A NAME="getClassificationType()"><!-- --></A><H3>getClassificationType</H3><PRE>public <A HREF="../../../../weka/core/SelectedTag.html" title="class in weka.core">SelectedTag</A> <B>getClassificationType</B>()</PRE><DL><DD>Returns the classification type.<P><DD><DL></DL></DD><DD><DL><DT><B>Returns:</B><DD>the classification type</DL></DD></DL><HR><A NAME="tuneInterpolationParameterTipText()"><!-- --></A><H3>tuneInterpolationParameterTipText</H3><PRE>public java.lang.String <B>tuneInterpolationParameterTipText</B>()</PRE><DL><DD>Returns the tip text for this property.<P><DD><DL></DL></DD><DD><DL><DT><B>Returns:</B><DD>tip text for this property suitable for
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