ensembleselectionlibrarymodel.html

weka是机器学习和数据挖掘领域最有影响力的开源项目之一

</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>seed</CODE> - the seed value</DL>
</DD>
</DL>
<HR>

<A NAME="getSeed()"><!-- --></A><H3>
getSeed</H3>
<PRE>
public int <B>getSeed</B>()</PRE>
<DL>
<DD>Get the seed
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>

<DT><B>Returns:</B><DD>the seed value</DL>
</DD>
</DL>
<HR>

<A NAME="setValidationRatio(double)"><!-- --></A><H3>
setValidationRatio</H3>
<PRE>
public void <B>setValidationRatio</B>(double&nbsp;validationRatio)</PRE>
<DL>
<DD>Sets the validation set ratio (only meaningful if folds == 1)
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>validationRatio</CODE> - the new ration</DL>
</DD>
</DL>
<HR>

<A NAME="getValidationRatio()"><!-- --></A><H3>
getValidationRatio</H3>
<PRE>
public double <B>getValidationRatio</B>()</PRE>
<DL>
<DD>get validationRatio
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>

<DT><B>Returns:</B><DD>the current ratio</DL>
</DD>
</DL>
<HR>

<A NAME="setFolds(int)"><!-- --></A><H3>
setFolds</H3>
<PRE>
public void <B>setFolds</B>(int&nbsp;folds)</PRE>
<DL>
<DD>Set the number of folds for cross validation. The number of folds also
 indicates how many classifiers will be built to represent this model.
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>folds</CODE> - the number of folds to use</DL>
</DD>
</DL>
<HR>

<A NAME="getFolds()"><!-- --></A><H3>
getFolds</H3>
<PRE>
public int <B>getFolds</B>()</PRE>
<DL>
<DD>get the number of folds
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>

<DT><B>Returns:</B><DD>the current number of folds</DL>
</DD>
</DL>
<HR>

<A NAME="setChecksum(java.lang.String)"><!-- --></A><H3>
setChecksum</H3>
<PRE>
public void <B>setChecksum</B>(java.lang.String&nbsp;instancesChecksum)</PRE>
<DL>
<DD>set the checksum
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>instancesChecksum</CODE> - the new checksum</DL>
</DD>
</DL>
<HR>

<A NAME="getChecksum()"><!-- --></A><H3>
getChecksum</H3>
<PRE>
public java.lang.String <B>getChecksum</B>()</PRE>
<DL>
<DD>get the checksum
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>

<DT><B>Returns:</B><DD>the current checksum</DL>
</DD>
</DL>
<HR>

<A NAME="getModels()"><!-- --></A><H3>
getModels</H3>
<PRE>
public <A HREF="../../../../weka/classifiers/Classifier.html" title="class in weka.classifiers">Classifier</A>[] <B>getModels</B>()</PRE>
<DL>
<DD>Returs the array of classifiers
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>

<DT><B>Returns:</B><DD>the current models</DL>
</DD>
</DL>
<HR>

<A NAME="setFileName(java.lang.String)"><!-- --></A><H3>
setFileName</H3>
<PRE>
public void <B>setFileName</B>(java.lang.String&nbsp;fileName)</PRE>
<DL>
<DD>Sets the .elm file name for this library model
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>fileName</CODE> - the new filename</DL>
</DD>
</DL>
<HR>

<A NAME="getStringChecksum(java.lang.String)"><!-- --></A><H3>
getStringChecksum</H3>
<PRE>
public static java.lang.String <B>getStringChecksum</B>(java.lang.String&nbsp;string)</PRE>
<DL>
<DD>Gets a checksum for the string defining this classifier. This is used to
 preserve uniqueness in the classifier names.
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>string</CODE> - the classifier definition
<DT><B>Returns:</B><DD>the checksum string</DL>
</DD>
</DL>
<HR>

<A NAME="getFileName(java.lang.String)"><!-- --></A><H3>
getFileName</H3>
<PRE>
public static java.lang.String <B>getFileName</B>(java.lang.String&nbsp;stringRepresentation)</PRE>
<DL>
<DD>The purpose of this method is to get an appropriate file name for a model
 based on its string representation of a model. All generated filenames
 are limited to less than 128 characters and all of them will end with a
 64 bit checksum value of their string representation to try to maintain
 some uniqueness of file names.
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>stringRepresentation</CODE> - string representation of model
<DT><B>Returns:</B><DD>unique filename</DL>
</DD>
</DL>
<HR>

<A NAME="saveModel(java.lang.String, weka.classifiers.meta.ensembleSelection.EnsembleSelectionLibraryModel)"><!-- --></A><H3>
saveModel</H3>
<PRE>
public static void <B>saveModel</B>(java.lang.String&nbsp;directory,
                             <A HREF="../../../../weka/classifiers/meta/ensembleSelection/EnsembleSelectionLibraryModel.html" title="class in weka.classifiers.meta.ensembleSelection">EnsembleSelectionLibraryModel</A>&nbsp;model)</PRE>
<DL>
<DD>Saves the given model to the specified file.
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>directory</CODE> - the directory to save the model to<DD><CODE>model</CODE> - the model to save</DL>
</DD>
</DL>
<HR>

<A NAME="loadModel(java.lang.String)"><!-- --></A><H3>
loadModel</H3>
<PRE>
public static <A HREF="../../../../weka/classifiers/meta/ensembleSelection/EnsembleSelectionLibraryModel.html" title="class in weka.classifiers.meta.ensembleSelection">EnsembleSelectionLibraryModel</A> <B>loadModel</B>(java.lang.String&nbsp;modelFilePath)</PRE>
<DL>
<DD>loads the specified model
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>modelFilePath</CODE> - the path of the model
<DT><B>Returns:</B><DD>the model</DL>
</DD>
</DL>
<HR>

<A NAME="getValidationPredictions()"><!-- --></A><H3>
getValidationPredictions</H3>
<PRE>
public double[][] <B>getValidationPredictions</B>()</PRE>
<DL>
<DD>getter for validation predictions
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>

<DT><B>Returns:</B><DD>the current validation predictions</DL>
</DD>
</DL>
<HR>

<A NAME="setValidationPredictions(double[][])"><!-- --></A><H3>
setValidationPredictions</H3>
<PRE>
public void <B>setValidationPredictions</B>(double[][]&nbsp;predictions)</PRE>
<DL>
<DD>setter for validation predictions
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>predictions</CODE> - the new validation predictions</DL>
</DD>
</DL>
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