apriori.html

< 数据挖掘--实用机器学习技术及java实现> 一书结合数据挖掘和机器学习的知识,作者陈述了自动挖掘模式的基础理论,并且以java语言实现了具有代表性的各类数据挖掘方法.例如:class

<A NAME="TAGS_SELECTION"><!-- --></A><H3>
TAGS_SELECTION</H3>
<PRE>
public static final <A HREF="../../weka/core/Tag.html">Tag</A>[] <B>TAGS_SELECTION</B></PRE>
<DL>
</DL>
<HR>

<A NAME="m_metricType"><!-- --></A><H3>
m_metricType</H3>
<PRE>
protected int <B>m_metricType</B></PRE>
<DL>
<DD>The selected metric type.</DL>
<HR>

<A NAME="m_minMetric"><!-- --></A><H3>
m_minMetric</H3>
<PRE>
protected double <B>m_minMetric</B></PRE>
<DL>
<DD>The minimum metric score.</DL>
<HR>

<A NAME="m_numRules"><!-- --></A><H3>
m_numRules</H3>
<PRE>
protected int <B>m_numRules</B></PRE>
<DL>
<DD>The maximum number of rules that are output.</DL>
<HR>

<A NAME="m_delta"><!-- --></A><H3>
m_delta</H3>
<PRE>
protected double <B>m_delta</B></PRE>
<DL>
<DD>Delta by which m_minSupport is decreased in each iteration.</DL>
<HR>

<A NAME="m_significanceLevel"><!-- --></A><H3>
m_significanceLevel</H3>
<PRE>
protected double <B>m_significanceLevel</B></PRE>
<DL>
<DD>Significance level for optional significance test.</DL>
<HR>

<A NAME="m_cycles"><!-- --></A><H3>
m_cycles</H3>
<PRE>
protected int <B>m_cycles</B></PRE>
<DL>
<DD>Number of cycles used before required number of rules was one.</DL>
<HR>

<A NAME="m_Ls"><!-- --></A><H3>
m_Ls</H3>
<PRE>
protected <A HREF="../../weka/core/FastVector.html">FastVector</A> <B>m_Ls</B></PRE>
<DL>
<DD>The set of all sets of itemsets L.</DL>
<HR>

<A NAME="m_hashtables"><!-- --></A><H3>
m_hashtables</H3>
<PRE>
protected <A HREF="../../weka/core/FastVector.html">FastVector</A> <B>m_hashtables</B></PRE>
<DL>
<DD>The same information stored in hash tables.</DL>
<HR>

<A NAME="m_allTheRules"><!-- --></A><H3>
m_allTheRules</H3>
<PRE>
protected <A HREF="../../weka/core/FastVector.html">FastVector</A>[] <B>m_allTheRules</B></PRE>
<DL>
<DD>The list of all generated rules.</DL>
<HR>

<A NAME="m_instances"><!-- --></A><H3>
m_instances</H3>
<PRE>
protected <A HREF="../../weka/core/Instances.html">Instances</A> <B>m_instances</B></PRE>
<DL>
<DD>The instances (transactions) to be used for generating 
the association rules.</DL>
<HR>

<A NAME="m_outputItemSets"><!-- --></A><H3>
m_outputItemSets</H3>
<PRE>
protected boolean <B>m_outputItemSets</B></PRE>
<DL>
<DD>Output itemsets found?</DL>
<HR>

<A NAME="m_removeMissingCols"><!-- --></A><H3>
m_removeMissingCols</H3>
<PRE>
protected boolean <B>m_removeMissingCols</B></PRE>
<DL>
</DL>
<HR>

<A NAME="m_verbose"><!-- --></A><H3>
m_verbose</H3>
<PRE>
protected boolean <B>m_verbose</B></PRE>
<DL>
<DD>Report progress iteratively</DL>

<!-- ========= CONSTRUCTOR DETAIL ======== -->

<A NAME="constructor_detail"><!-- --></A>
<TABLE BORDER="1" CELLPADDING="3" CELLSPACING="0" WIDTH="100%">
<TR BGCOLOR="#CCCCFF" CLASS="TableHeadingColor">
<TD COLSPAN=1><FONT SIZE="+2">
<B>Constructor Detail</B></FONT></TD>
</TR>
</TABLE>

<A NAME="Apriori()"><!-- --></A><H3>
Apriori</H3>
<PRE>
public <B>Apriori</B>()</PRE>
<DL>
<DD>Constructor that allows to sets default values for the 
 minimum confidence and the maximum number of rules
 the minimum confidence.</DL>

<!-- ============ METHOD DETAIL ========== -->

<A NAME="method_detail"><!-- --></A>
<TABLE BORDER="1" CELLPADDING="3" CELLSPACING="0" WIDTH="100%">
<TR BGCOLOR="#CCCCFF" CLASS="TableHeadingColor">
<TD COLSPAN=1><FONT SIZE="+2">
<B>Method Detail</B></FONT></TD>
</TR>
</TABLE>

<A NAME="globalInfo()"><!-- --></A><H3>
globalInfo</H3>
<PRE>
public java.lang.String <B>globalInfo</B>()</PRE>
<DL>
<DD>Returns a string describing this associator<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Returns:</B><DD>a description of the evaluator suitable for
 displaying in the explorer/experimenter gui</DL>
</DD>
</DL>
<HR>

<A NAME="resetOptions()"><!-- --></A><H3>
resetOptions</H3>
<PRE>
public void <B>resetOptions</B>()</PRE>
<DL>
<DD>Resets the options to the default values.<DD><DL>
</DL>
</DD>
</DL>
<HR>

<A NAME="buildAssociations(weka.core.Instances)"><!-- --></A><H3>
buildAssociations</H3>
<PRE>
public void <B>buildAssociations</B>(<A HREF="../../weka/core/Instances.html">Instances</A>&nbsp;instances)
                       throws java.lang.Exception</PRE>
<DL>
<DD>Method that generates all large itemsets with a minimum support, and from
 these all association rules with a minimum confidence.<DD><DL>
<DT><B>Overrides:</B><DD><CODE><A HREF="../../weka/associations/Associator.html#buildAssociations(weka.core.Instances)">buildAssociations</A></CODE> in class <CODE><A HREF="../../weka/associations/Associator.html">Associator</A></CODE></DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>instances</CODE> - the instances to be used for generating the associations<DT><B>Throws:</B><DD><CODE>java.lang.Exception</CODE> - if rules can't be built successfully</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<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">OptionHandler</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. Valid options are:<p>
   
 -N required number of rules <br>
 The required number of rules (default: 10). <p>

 -T type of metric by which to sort rules <br>
 0 = confidence | 1 = lift | 2 = leverage | 3 = Conviction. <p>

 -C minimum metric score of a rule <br>
 The minimum confidence of a rule (default: 0.9). <p>

 -D delta for minimum support <br>
 The delta by which the minimum support is decreased in
 each iteration (default: 0.05).

 -U upper bound for minimum support <br>
 The upper bound for minimum support. Don't explicitly look for 
 rules with more than this level of support. <p>

 -M lower bound for minimum support <br>
 The lower bound for the minimum support (default = 0.1). <p>

 -S significance level <br>
 If used, rules are tested for significance at
 the given level. Slower (default = no significance testing). <p>

 -I <br>
 If set the itemsets found are also output (default = no). <p>

 -V <br>
 If set then progress is reported iteratively during execution. <p>

 -R <br>
 If set then columns that contain all missing values are removed from
 the data. <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">OptionHandler</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 Apriori object.<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">OptionHandler</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="toString()"><!-- --></A><H3>
toString</H3>
<PRE>
public java.lang.String <B>toString</B>()</PRE>
<DL>
<DD>Outputs the size of all the generated sets of itemsets and the rules.<DD><DL>
<DT><B>Overrides:</B><DD><CODE>toString</CODE> in class <CODE>java.lang.Object</CODE></DL>
</DD>
</DL>
<HR>

<A NAME="removeAllMissingColsTipText()"><!-- --></A><H3>
removeAllMissingColsTipText</H3>
<PRE>
public java.lang.String <B>removeAllMissingColsTipText</B>()</PRE>
<DL>
<DD>Returns the tip text for this property<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="setRemoveAllMissingCols(boolean)"><!-- --></A><H3>
setRemoveAllMissingCols</H3>
<PRE>
public void <B>setRemoveAllMissingCols</B>(boolean&nbsp;r)</PRE>
<DL>
<DD>Remove columns containing all missing values.<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Parameters:</B><DD><CODE>r</CODE> - true if cols are to be removed.</DL>
</DD>
</DL>
<HR>

<A NAME="getRemoveAllMissingCols()"><!-- --></A><H3>
getRemoveAllMissingCols</H3>
<PRE>
public boolean <B>getRemoveAllMissingCols</B>()</PRE>
<DL>
<DD>Returns whether columns containing all missing values are to be removed<DD><DL>
</DL>
</DD>
<DD><DL>
<DT><B>Returns:</B><DD>true if columns are to be removed.</DL>
</DD>
</DL>
<HR>

<A NAME="upperBoundMinSupportTipText()"><!-- --></A><H3>
upperBoundMinSupportTipText</H3>
<PRE>
public java.lang.String <B>upperBoundMinSupportTipText</B>()</PRE>
<DL>
<DD>Returns the tip text for this property<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="getUpperBoundMinSupport()"><!-- --></A><H3>
getUpperBoundMinSupport</H3>
<PRE>
public double <B>getUpperBoundMinSupport</B>()</PRE>
<DL>
<DD>Get the value of upperBoundMinSupport.<DD><DL>
</DL>
</DD>