ft.html

数据挖掘的最常用工具。由于开源

<DT><B>Returns:</B><DD>the class probabilities
<DT><B>Throws:</B>
<DD><CODE>java.lang.Exception</CODE> - if distribution can't be computed successfully</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>&nbsp;instance)
                        throws java.lang.Exception</PRE>
<DL>
<DD>Classifies an instance.
<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 classify
<DT><B>Returns:</B><DD>the classification
<DT><B>Throws:</B>
<DD><CODE>java.lang.Exception</CODE> - if instance can't be classified successfully</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 classifier.
<P>
<DD><DL>
<DT><B>Overrides:</B><DD><CODE>toString</CODE> in class <CODE>java.lang.Object</CODE></DL>
</DD>
<DD><DL>

<DT><B>Returns:</B><DD>a string representation of the classifier</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/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 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> -B
  Binary splits (convert nominal attributes to binary ones) </pre>
 
 <pre> -P
  Use error on probabilities instead of misclassification error for stopping criterion of LogitBoost.</pre>
 
 <pre> -I &lt;numIterations&gt;
  Set fixed number of iterations for LogitBoost (instead of using cross-validation)</pre>
 
 <pre> -F &lt;modelType&gt;
  Set Funtional Tree type to be generate:  0 for FT, 1 for FTLeaves and 2 for FTInner</pre>
 
 <pre> -M &lt;numInstances&gt;
  Set minimum number of instances at which a node can be split (default 15)</pre>
 
 <pre> -W &lt;beta&gt;
  Set beta for weight trimming for LogitBoost. Set to 0 (default) for no weight trimming.</pre>
 
 <pre> -A
  The AIC is used to choose the best iteration.</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 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/Classifier.html#getOptions()">getOptions</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 array of strings suitable for passing to setOptions</DL>
</DD>
</DL>
<HR>

<A NAME="getWeightTrimBeta()"><!-- --></A><H3>
getWeightTrimBeta</H3>
<PRE>
public double <B>getWeightTrimBeta</B>()</PRE>
<DL>
<DD>Get the value of weightTrimBeta.
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>
</DL>
</DD>
</DL>
<HR>

<A NAME="getUseAIC()"><!-- --></A><H3>
getUseAIC</H3>
<PRE>
public boolean <B>getUseAIC</B>()</PRE>
<DL>
<DD>Get the value of useAIC.
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>

<DT><B>Returns:</B><DD>Value of useAIC.</DL>
</DD>
</DL>
<HR>

<A NAME="setWeightTrimBeta(double)"><!-- --></A><H3>
setWeightTrimBeta</H3>
<PRE>
public void <B>setWeightTrimBeta</B>(double&nbsp;n)</PRE>
<DL>
<DD>Set the value of weightTrimBeta.
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>
</DL>
</DD>
</DL>
<HR>

<A NAME="setUseAIC(boolean)"><!-- --></A><H3>
setUseAIC</H3>
<PRE>
public void <B>setUseAIC</B>(boolean&nbsp;c)</PRE>
<DL>
<DD>Set the value of useAIC.
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>c</CODE> - Value to assign to useAIC.</DL>
</DD>
</DL>
<HR>

<A NAME="getBinSplit()"><!-- --></A><H3>
getBinSplit</H3>
<PRE>
public boolean <B>getBinSplit</B>()</PRE>
<DL>
<DD>Get the value of binarySplits.
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>

<DT><B>Returns:</B><DD>Value of binarySplits.</DL>
</DD>
</DL>
<HR>

<A NAME="getErrorOnProbabilities()"><!-- --></A><H3>
getErrorOnProbabilities</H3>
<PRE>
public boolean <B>getErrorOnProbabilities</B>()</PRE>
<DL>
<DD>Get the value of errorOnProbabilities.
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>

<DT><B>Returns:</B><DD>Value of errorOnProbabilities.</DL>
</DD>
</DL>
<HR>

<A NAME="getNumBoostingIterations()"><!-- --></A><H3>
getNumBoostingIterations</H3>
<PRE>
public int <B>getNumBoostingIterations</B>()</PRE>
<DL>
<DD>Get the value of numBoostingIterations.
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>

<DT><B>Returns:</B><DD>Value of numBoostingIterations.</DL>
</DD>
</DL>
<HR>

<A NAME="getModelType()"><!-- --></A><H3>
getModelType</H3>
<PRE>
public <A HREF="../../../weka/core/SelectedTag.html" title="class in weka.core">SelectedTag</A> <B>getModelType</B>()</PRE>
<DL>
<DD>Get the type of functional tree model being used.
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>

<DT><B>Returns:</B><DD>the type of functional tree model.</DL>
</DD>
</DL>
<HR>

<A NAME="setModelType(weka.core.SelectedTag)"><!-- --></A><H3>
setModelType</H3>
<PRE>
public void <B>setModelType</B>(<A HREF="../../../weka/core/SelectedTag.html" title="class in weka.core">SelectedTag</A>&nbsp;newMethod)</PRE>
<DL>
<DD>Set the Functional Tree type.
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>c</CODE> - Value corresponding to tree type.</DL>
</DD>
</DL>
<HR>

<A NAME="getMinNumInstances()"><!-- --></A><H3>
getMinNumInstances</H3>
<PRE>
public int <B>getMinNumInstances</B>()</PRE>
<DL>
<DD>Get the value of minNumInstances.
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>

<DT><B>Returns:</B><DD>Value of minNumInstances.</DL>
</DD>
</DL>
<HR>

<A NAME="setBinSplit(boolean)"><!-- --></A><H3>
setBinSplit</H3>
<PRE>
public void <B>setBinSplit</B>(boolean&nbsp;c)</PRE>
<DL>
<DD>Set the value of binarySplits.
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>c</CODE> - Value to assign to binarySplits.</DL>
</DD>
</DL>
<HR>

<A NAME="setErrorOnProbabilities(boolean)"><!-- --></A><H3>
setErrorOnProbabilities</H3>
<PRE>
public void <B>setErrorOnProbabilities</B>(boolean&nbsp;c)</PRE>
<DL>
<DD>Set the value of errorOnProbabilities.
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>c</CODE> - Value to assign to errorOnProbabilities.</DL>
</DD>
</DL>
<HR>

<A NAME="setNumBoostingIterations(int)"><!-- --></A><H3>
setNumBoostingIterations</H3>
<PRE>
public void <B>setNumBoostingIterations</B>(int&nbsp;c)</PRE>
<DL>
<DD>Set the value of numBoostingIterations.
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>c</CODE> - Value to assign to numBoostingIterations.</DL>
</DD>
</DL>
<HR>

<A NAME="setMinNumInstances(int)"><!-- --></A><H3>
setMinNumInstances</H3>
<PRE>
public void <B>setMinNumInstances</B>(int&nbsp;c)</PRE>
<DL>
<DD>Set the value of minNumInstances.
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>c</CODE> - Value to assign to minNumInstances.</DL>
</DD>
</DL>
<HR>

<A NAME="graphType()"><!-- --></A><H3>
graphType</H3>
<PRE>
public int <B>graphType</B>()</PRE>
<DL>
<DD>Returns the type of graph this classifier
  represents.