discretedistribution.html

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<A NAME="DiscreteDistribution(weka.classifiers.misc.monotone.CumulativeDiscreteDistribution)"><!-- --></A><H3>
DiscreteDistribution</H3>
<PRE>
public <B>DiscreteDistribution</B>(<A HREF="../../../../weka/classifiers/misc/monotone/CumulativeDiscreteDistribution.html" title="class in weka.classifiers.misc.monotone">CumulativeDiscreteDistribution</A>&nbsp;cdf)</PRE>
<DL>
<DD>Create a <code> DiscreteDistribution </code> based on a 
 <code> CumulativeDiscreteDistribution. </code>
<P>
<DL>
<DT><B>Parameters:</B><DD><CODE>cdf</CODE> - the <code> CumulativeDiscreteDistribution </code></DL>
</DL>
<HR>

<A NAME="DiscreteDistribution(double[])"><!-- --></A><H3>
DiscreteDistribution</H3>
<PRE>
public <B>DiscreteDistribution</B>(double[]&nbsp;dd)
                     throws java.lang.IllegalArgumentException</PRE>
<DL>
<DD>Create a <code> DiscreteDistribution </code> based on an 
 array of doubles.
<P>
<DL>
<DT><B>Parameters:</B><DD><CODE>dd</CODE> - the array of doubles representing a valid 
 discrete distribution
<DT><B>Throws:</B>
<DD><CODE>java.lang.IllegalArgumentException</CODE> - if <code> dd </code>
 does not represent a valid discrete distribution</DL>
</DL>

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<A NAME="getNumSymbols()"><!-- --></A><H3>
getNumSymbols</H3>
<PRE>
public int <B>getNumSymbols</B>()</PRE>
<DL>
<DD>Get the number of elements over which the <code>
 DiscreteDistribution </code> is defined.
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>

<DT><B>Returns:</B><DD>the number of elements over which the <code>
 DiscreteDistribution </code> is defined</DL>
</DD>
</DL>
<HR>

<A NAME="getProbability(int)"><!-- --></A><H3>
getProbability</H3>
<PRE>
public double <B>getProbability</B>(int&nbsp;index)</PRE>
<DL>
<DD>Get the probability of finding the element at
 a specified index.
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>index</CODE> - the index of the required element
<DT><B>Returns:</B><DD>the probability of finding the specified element</DL>
</DD>
</DL>
<HR>

<A NAME="mean()"><!-- --></A><H3>
mean</H3>
<PRE>
public double <B>mean</B>()</PRE>
<DL>
<DD>Calculate the mean of the distribution.  The scores for
 calculating the mean start from 0 and have step size one,
 i.e. if there are n elements then the scores are 0,1,...,n-1.
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>

<DT><B>Returns:</B><DD>the mean of the distribution</DL>
</DD>
</DL>
<HR>

<A NAME="median()"><!-- --></A><H3>
median</H3>
<PRE>
public double <B>median</B>()</PRE>
<DL>
<DD>Calculate the median of the distribution.  This means
 the following: if there is a label m such that 
 P(x &lt;= m) &gt;= &frac12; and
 P(x &gt;= m) &gt;= &frac12;  then this label is returned.
 If there is no such label, an interpolation between the
 smallest label satisfying the first condition and the
 largest label satisfying the second condition is performed.
 The returned value is thus either an element label, or
 exactly between two element labels.
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>

<DT><B>Returns:</B><DD>the median of the distribution.</DL>
</DD>
</DL>
<HR>

<A NAME="modes()"><!-- --></A><H3>
modes</H3>
<PRE>
public int[] <B>modes</B>()</PRE>
<DL>
<DD>Get a sorted array containing the indices of the elements with
 maximal probability.
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>

<DT><B>Returns:</B><DD>an array of class indices with maximal probability.</DL>
</DD>
</DL>
<HR>

<A NAME="toArray()"><!-- --></A><H3>
toArray</H3>
<PRE>
public double[] <B>toArray</B>()</PRE>
<DL>
<DD>Convert the <code> DiscreteDistribution </code> to an
 array of doubles.
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>

<DT><B>Returns:</B><DD>an array of doubles representing the
 <code> DiscreteDistribution </code></DL>
</DD>
</DL>
<HR>

<A NAME="toString()"><!-- --></A><H3>
toString</H3>
<PRE>
public java.lang.String <B>toString</B>()</PRE>
<DL>
<DD>Get a string representation of the given <code>
 DiscreteDistribution. </code>
<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 this object</DL>
</DD>
</DL>
<HR>

<A NAME="stochasticDominatedBy(weka.classifiers.misc.monotone.DiscreteDistribution)"><!-- --></A><H3>
stochasticDominatedBy</H3>
<PRE>
public boolean <B>stochasticDominatedBy</B>(<A HREF="../../../../weka/classifiers/misc/monotone/DiscreteDistribution.html" title="class in weka.classifiers.misc.monotone">DiscreteDistribution</A>&nbsp;dd)
                              throws java.lang.IllegalArgumentException</PRE>
<DL>
<DD>Checks if <code> this </code> is dominated by <code> dd. </code>
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>dd</CODE> - the DiscreteDistribution to compare to
<DT><B>Returns:</B><DD><code> true </code> if <code> this </code> is dominated by 
 <code> dd </code>, <code> false </code> otherwise
<DT><B>Throws:</B>
<DD><CODE>java.lang.IllegalArgumentException</CODE> - if the two distributions don't
 have the same length</DL>
</DD>
</DL>
<HR>

<A NAME="getRevision()"><!-- --></A><H3>
getRevision</H3>
<PRE>
public java.lang.String <B>getRevision</B>()</PRE>
<DL>
<DD>Returns the revision string.
<P>
<DD><DL>
<DT><B>Specified by:</B><DD><CODE><A HREF="../../../../weka/core/RevisionHandler.html#getRevision()">getRevision</A></CODE> in interface <CODE><A HREF="../../../../weka/core/RevisionHandler.html" title="interface in weka.core">RevisionHandler</A></CODE></DL>
</DD>
<DD><DL>

<DT><B>Returns:</B><DD>the revision</DL>
</DD>
</DL>
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