carulegeneration.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

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<TD><CODE><A HREF="../../weka/associations/RuleGeneration.html#binomialDistribution(double, double, double)">binomialDistribution</A>, <A HREF="../../weka/associations/RuleGeneration.html#change()">change</A>, <A HREF="../../weka/associations/RuleGeneration.html#count()">count</A>, <A HREF="../../weka/associations/RuleGeneration.html#expectation(double, int, double[], java.util.Hashtable)">expectation</A>, <A HREF="../../weka/associations/RuleGeneration.html#removeRedundant(weka.associations.RuleItem)">removeRedundant</A>, <A HREF="../../weka/associations/RuleGeneration.html#singleConsequence(weka.core.Instances, int, weka.core.FastVector)">singleConsequence</A></CODE></TD>
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<A NAME="CaRuleGeneration(weka.associations.ItemSet)"><!-- --></A><H3>
CaRuleGeneration</H3>
<PRE>
public <B>CaRuleGeneration</B>(<A HREF="../../weka/associations/ItemSet.html" title="class in weka.associations">ItemSet</A>&nbsp;itemSet)</PRE>
<DL>
<DD>Constructor
<P>
<DL>
<DT><B>Parameters:</B><DD><CODE>itemSet</CODE> - the item set that forms the premise of the rule</DL>
</DL>

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<A NAME="generateRules(int, double[], java.util.Hashtable, double, weka.core.Instances, java.util.TreeSet, int)"><!-- --></A><H3>
generateRules</H3>
<PRE>
public java.util.TreeSet <B>generateRules</B>(int&nbsp;numRules,
                                       double[]&nbsp;midPoints,
                                       java.util.Hashtable&nbsp;priors,
                                       double&nbsp;expectation,
                                       <A HREF="../../weka/core/Instances.html" title="class in weka.core">Instances</A>&nbsp;instances,
                                       java.util.TreeSet&nbsp;best,
                                       int&nbsp;genTime)</PRE>
<DL>
<DD>Generates all rules for an item set. The item set is the premise.
<P>
<DD><DL>
<DT><B>Overrides:</B><DD><CODE><A HREF="../../weka/associations/RuleGeneration.html#generateRules(int, double[], java.util.Hashtable, double, weka.core.Instances, java.util.TreeSet, int)">generateRules</A></CODE> in class <CODE><A HREF="../../weka/associations/RuleGeneration.html" title="class in weka.associations">RuleGeneration</A></CODE></DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>numRules</CODE> - the number of association rules the use wants to mine.
 This number equals the size <i>n<\i> of the list of the
 best rules.<DD><CODE>midPoints</CODE> - the mid points of the intervals<DD><CODE>priors</CODE> - Hashtable that contains the prior probabilities<DD><CODE>expectation</CODE> - the minimum value of the expected predictive accuracy
 that is needed to get into the list of the best rules<DD><CODE>instances</CODE> - the instances for which association rules are generated<DD><CODE>best</CODE> - the list of the <i>n<\i> best rules.
 The list is implemented as a TreeSet<DD><CODE>genTime</CODE> - the maximum time of generation
<DT><B>Returns:</B><DD>all the rules with minimum confidence for the given item set</DL>
</DD>
</DL>
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<A NAME="aSubsumesB(weka.associations.RuleItem, weka.associations.RuleItem)"><!-- --></A><H3>
aSubsumesB</H3>
<PRE>
public static boolean <B>aSubsumesB</B>(<A HREF="../../weka/associations/RuleItem.html" title="class in weka.associations">RuleItem</A>&nbsp;a,
                                 <A HREF="../../weka/associations/RuleItem.html" title="class in weka.associations">RuleItem</A>&nbsp;b)</PRE>
<DL>
<DD>Methods that decides whether or not rule a subsumes rule b.
 The defintion of subsumption is:
 Rule a subsumes rule b, if a subsumes b
 AND
 a has got least the same expected predictive accuracy as b.
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>a</CODE> - an association rule stored as a RuleItem<DD><CODE>b</CODE> - an association rule stored as a RuleItem
<DT><B>Returns:</B><DD>true if rule a subsumes rule b or false otherwise.</DL>
</DD>
</DL>
<HR>

<A NAME="singletons(weka.core.Instances)"><!-- --></A><H3>
singletons</H3>
<PRE>
public static <A HREF="../../weka/core/FastVector.html" title="class in weka.core">FastVector</A> <B>singletons</B>(<A HREF="../../weka/core/Instances.html" title="class in weka.core">Instances</A>&nbsp;instances)
                             throws java.lang.Exception</PRE>
<DL>
<DD>Converts the header info of the given set of instances into a set 
 of item sets (singletons). The ordering of values in the header file 
 determines the lexicographic order.
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>instances</CODE> - the set of instances whose header info is to be used
<DT><B>Returns:</B><DD>a set of item sets, each containing a single item
<DT><B>Throws:</B>
<DD><CODE>java.lang.Exception</CODE> - if singletons can't be generated successfully</DL>
</DD>
</DL>
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<A NAME="singleConsequence(weka.core.Instances)"><!-- --></A><H3>
singleConsequence</H3>
<PRE>
public static <A HREF="../../weka/core/FastVector.html" title="class in weka.core">FastVector</A> <B>singleConsequence</B>(<A HREF="../../weka/core/Instances.html" title="class in weka.core">Instances</A>&nbsp;instances)</PRE>
<DL>
<DD>generates a consequence of length 1 for a class association rule.
<P>
<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>instances</CODE> - the instances under consideration
<DT><B>Returns:</B><DD>FastVector with consequences of length 1</DL>
</DD>
</DL>
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