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<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.0 Frameset//EN""http://www.w3.org/TR/REC-html40/frameset.dtd"><!--NewPage--><HTML><HEAD><!-- Generated by javadoc on Wed Sep 04 10:31:49 CDT 2002 --><TITLE>: Class NaiveBayes</TITLE><LINK REL ="stylesheet" TYPE="text/css" HREF="../../stylesheet.css" TITLE="Style"></HEAD><BODY BGCOLOR="white"><!-- ========== START OF NAVBAR ========== --><A NAME="navbar_top"><!-- --></A><TABLE BORDER="0" WIDTH="100%" CELLPADDING="1" CELLSPACING="0"><TR><TD COLSPAN=2 BGCOLOR="#EEEEFF" CLASS="NavBarCell1"><A NAME="navbar_top_firstrow"><!-- --></A><TABLE BORDER="0" CELLPADDING="0" CELLSPACING="3"> <TR ALIGN="center" VALIGN="top"> <TD BGCOLOR="#EEEEFF" CLASS="NavBarCell1"> <A HREF="../../overview-summary.html"><FONT CLASS="NavBarFont1"><B>Overview</B></FONT></A> </TD> <TD BGCOLOR="#EEEEFF" CLASS="NavBarCell1"> <A HREF="package-summary.html"><FONT CLASS="NavBarFont1"><B>Package</B></FONT></A> </TD> <TD BGCOLOR="#FFFFFF" CLASS="NavBarCell1Rev"> <FONT CLASS="NavBarFont1Rev"><B>Class</B></FONT> </TD> <TD BGCOLOR="#EEEEFF" CLASS="NavBarCell1"> <A HREF="package-tree.html"><FONT CLASS="NavBarFont1"><B>Tree</B></FONT></A> </TD> <TD BGCOLOR="#EEEEFF" CLASS="NavBarCell1"> <A HREF="../../deprecated-list.html"><FONT CLASS="NavBarFont1"><B>Deprecated</B></FONT></A> </TD> <TD BGCOLOR="#EEEEFF" CLASS="NavBarCell1"> <A HREF="../../index-all.html"><FONT CLASS="NavBarFont1"><B>Index</B></FONT></A> </TD> <TD BGCOLOR="#EEEEFF" CLASS="NavBarCell1"> <A HREF="../../help-doc.html"><FONT CLASS="NavBarFont1"><B>Help</B></FONT></A> </TD> </TR></TABLE></TD><TD ALIGN="right" VALIGN="top" ROWSPAN=3><EM></EM></TD></TR><TR><TD BGCOLOR="white" CLASS="NavBarCell2"><FONT SIZE="-2"> <A HREF="../../weka/classifiers/MultiScheme.html"><B>PREV CLASS</B></A> <A HREF="../../weka/classifiers/NaiveBayesSimple.html"><B>NEXT CLASS</B></A></FONT></TD><TD BGCOLOR="white" CLASS="NavBarCell2"><FONT SIZE="-2"> <A HREF="../../index.html" TARGET="_top"><B>FRAMES</B></A> <A HREF="NaiveBayes.html" TARGET="_top"><B>NO FRAMES</B></A></FONT></TD></TR><TR><TD VALIGN="top" CLASS="NavBarCell3"><FONT SIZE="-2"> SUMMARY: INNER | <A HREF="#field_summary">FIELD</A> | <A HREF="#constructor_summary">CONSTR</A> | <A HREF="#method_summary">METHOD</A></FONT></TD><TD VALIGN="top" CLASS="NavBarCell3"><FONT SIZE="-2">DETAIL: <A HREF="#field_detail">FIELD</A> | <A HREF="#constructor_detail">CONSTR</A> | <A HREF="#method_detail">METHOD</A></FONT></TD></TR></TABLE><!-- =========== END OF NAVBAR =========== --><HR><!-- ======== START OF CLASS DATA ======== --><H2><FONT SIZE="-1">weka.classifiers</FONT><BR>Class NaiveBayes</H2><PRE>java.lang.Object | +--<A HREF="../../weka/classifiers/Classifier.html">weka.classifiers.Classifier</A> | +--<A HREF="../../weka/classifiers/DistributionClassifier.html">weka.classifiers.DistributionClassifier</A> | +--<B>weka.classifiers.NaiveBayes</B></PRE><DL><DT><B>All Implemented Interfaces:</B> <DD>java.lang.Cloneable, <A HREF="../../weka/core/OptionHandler.html">OptionHandler</A>, java.io.Serializable, <A HREF="../../weka/core/WeightedInstancesHandler.html">WeightedInstancesHandler</A></DD></DL><HR><DL><DT>public class <B>NaiveBayes</B><DT>extends <A HREF="../../weka/classifiers/DistributionClassifier.html">DistributionClassifier</A><DT>implements <A HREF="../../weka/core/OptionHandler.html">OptionHandler</A>, <A HREF="../../weka/core/WeightedInstancesHandler.html">WeightedInstancesHandler</A></DL><P>Class for a Naive Bayes classifier using estimator classes. Numeric estimator precision values are chosen based on analysis of the training data. For this reason, the classifier is not an UpdateableClassifier (which in typical usage are initialized with zero training instances) -- if you need the UpdateableClassifier functionality, Create an empty class such as the following: <p> <pre><code> public class NaiveBayesUpdateable extends NaiveBayes implements UpdateableClassifier { } </code></pre> This classifier will use a default precision of 0.1 for numeric attributes when buildClassifier is called with zero training instances. <p> For more information on Naive Bayes classifiers, see<p> George H. John and Pat Langley (1995). <i>Estimating Continuous Distributions in Bayesian Classifiers</i>. Proceedings of the Eleventh Conference on Uncertainty in Artificial Intelligence. pp. 338-345. Morgan Kaufmann, San Mateo.<p> Valid options are:<p> -K <br> Use kernel estimation for modelling numeric attributes rather than a single normal distribution.<p><P><DL><DT><B>See Also: </B><DD><A HREF="../../serialized-form.html#weka.classifiers.NaiveBayes">Serialized Form</A></DL><HR><P><!-- ======== INNER CLASS SUMMARY ======== --><!-- =========== FIELD SUMMARY =========== --><A NAME="field_summary"><!-- --></A><TABLE BORDER="1" CELLPADDING="3" CELLSPACING="0" WIDTH="100%"><TR BGCOLOR="#CCCCFF" CLASS="TableHeadingColor"><TD COLSPAN=2><FONT SIZE="+2"><B>Field Summary</B></FONT></TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>protected static double</CODE></FONT></TD><TD><CODE><B><A HREF="../../weka/classifiers/NaiveBayes.html#DEFAULT_NUM_PRECISION">DEFAULT_NUM_PRECISION</A></B></CODE><BR> The precision parameter used for numeric attributes</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>protected <A HREF="../../weka/estimators/Estimator.html">Estimator</A></CODE></FONT></TD><TD><CODE><B><A HREF="../../weka/classifiers/NaiveBayes.html#m_ClassDistribution">m_ClassDistribution</A></B></CODE><BR> The class estimator.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>protected <A HREF="../../weka/estimators/Estimator.html">Estimator</A>[][]</CODE></FONT></TD><TD><CODE><B><A HREF="../../weka/classifiers/NaiveBayes.html#m_Distributions">m_Distributions</A></B></CODE><BR> The attribute estimators.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>protected <A HREF="../../weka/core/Instances.html">Instances</A></CODE></FONT></TD><TD><CODE><B><A HREF="../../weka/classifiers/NaiveBayes.html#m_Instances">m_Instances</A></B></CODE><BR> The dataset header for the purposes of printing out a semi-intelligible model</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>protected int</CODE></FONT></TD><TD><CODE><B><A HREF="../../weka/classifiers/NaiveBayes.html#m_NumClasses">m_NumClasses</A></B></CODE><BR> The number of classes (or 1 for numeric class)</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>protected boolean</CODE></FONT></TD><TD><CODE><B><A HREF="../../weka/classifiers/NaiveBayes.html#m_UseKernelEstimator">m_UseKernelEstimator</A></B></CODE><BR> Whether to use kernel density estimator rather than normal distribution for numeric attributes</TD></TR></TABLE> <!-- ======== CONSTRUCTOR SUMMARY ======== --><A NAME="constructor_summary"><!-- --></A><TABLE BORDER="1" CELLPADDING="3" CELLSPACING="0" WIDTH="100%"><TR BGCOLOR="#CCCCFF" CLASS="TableHeadingColor"><TD COLSPAN=2><FONT SIZE="+2"><B>Constructor Summary</B></FONT></TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><CODE><B><A HREF="../../weka/classifiers/NaiveBayes.html#NaiveBayes()">NaiveBayes</A></B>()</CODE><BR> </TD></TR></TABLE> <!-- ========== METHOD SUMMARY =========== --><A NAME="method_summary"><!-- --></A><TABLE BORDER="1" CELLPADDING="3" CELLSPACING="0" WIDTH="100%"><TR BGCOLOR="#CCCCFF" CLASS="TableHeadingColor"><TD COLSPAN=2><FONT SIZE="+2"><B>Method Summary</B></FONT></TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> void</CODE></FONT></TD><TD><CODE><B><A HREF="../../weka/classifiers/NaiveBayes.html#buildClassifier(weka.core.Instances)">buildClassifier</A></B>(<A HREF="../../weka/core/Instances.html">Instances</A> instances)</CODE><BR> Generates the classifier.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> double[]</CODE></FONT></TD><TD><CODE><B><A HREF="../../weka/classifiers/NaiveBayes.html#distributionForInstance(weka.core.Instance)">distributionForInstance</A></B>(<A HREF="../../weka/core/Instance.html">Instance</A> instance)</CODE><BR> Calculates the class membership probabilities for the given test instance.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> java.lang.String[]</CODE></FONT></TD><TD><CODE><B><A HREF="../../weka/classifiers/NaiveBayes.html#getOptions()">getOptions</A></B>()</CODE><BR> Gets the current settings of the classifier.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> boolean</CODE></FONT></TD><TD><CODE><B><A HREF="../../weka/classifiers/NaiveBayes.html#getUseKernelEstimator()">getUseKernelEstimator</A></B>()</CODE><BR> Gets if kernel estimator is being used.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> java.util.Enumeration</CODE></FONT></TD><TD><CODE><B><A HREF="../../weka/classifiers/NaiveBayes.html#listOptions()">listOptions</A></B>()</CODE><BR> Returns an enumeration describing the available options</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>static void</CODE></FONT></TD><TD><CODE><B><A HREF="../../weka/classifiers/NaiveBayes.html#main(java.lang.String[])">main</A></B>(java.lang.String[] argv)</CODE><BR> Main method for testing this class.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> void</CODE></FONT></TD><TD><CODE><B><A HREF="../../weka/classifiers/NaiveBayes.html#setOptions(java.lang.String[])">setOptions</A></B>(java.lang.String[] options)</CODE><BR> Parses a given list of options.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> void</CODE></FONT></TD><TD><CODE><B><A HREF="../../weka/classifiers/NaiveBayes.html#setUseKernelEstimator(boolean)">setUseKernelEstimator</A></B>(boolean v)</CODE><BR> Sets if kernel estimator is to be used.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> java.lang.String</CODE></FONT></TD><TD><CODE><B><A HREF="../../weka/classifiers/NaiveBayes.html#toString()">toString</A></B>()</CODE><BR> Returns a description of the classifier.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> void</CODE></FONT></TD><TD><CODE><B><A HREF="../../weka/classifiers/NaiveBayes.html#updateClassifier(weka.core.Instance)">updateClassifier</A></B>(<A HREF="../../weka/core/Instance.html">Instance</A> instance)</CODE><BR> Updates the classifier with the given instance.</TD></TR></TABLE> <A NAME="methods_inherited_from_class_weka.classifiers.DistributionClassifier"><!-- --></A><TABLE BORDER="1" CELLPADDING="3" CELLSPACING="0" WIDTH="100%"><TR BGCOLOR="#EEEEFF" CLASS="TableSubHeadingColor"><TD><B>Methods inherited from class weka.classifiers.<A HREF="../../weka/classifiers/DistributionClassifier.html">DistributionClassifier</A></B></TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><CODE><A HREF="../../weka/classifiers/DistributionClassifier.html#classifyInstance(weka.core.Instance)">classifyInstance</A></CODE></TD></TR></TABLE> <A NAME="methods_inherited_from_class_weka.classifiers.Classifier"><!-- --></A><TABLE BORDER="1" CELLPADDING="3" CELLSPACING="0" WIDTH="100%"><TR BGCOLOR="#EEEEFF" CLASS="TableSubHeadingColor"><TD><B>Methods inherited from class weka.classifiers.<A HREF="../../weka/classifiers/Classifier.html">Classifier</A></B></TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><CODE><A HREF="../../weka/classifiers/Classifier.html#forName(java.lang.String, java.lang.String[])">forName</A>, <A HREF="../../weka/classifiers/Classifier.html#makeCopies(weka.classifiers.Classifier, int)">makeCopies</A></CODE></TD></TR>⌨️ 快捷键说明
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