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<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN" "http://www.w3.org/TR/html4/loose.dtd"><!--NewPage--><HTML><HEAD><!-- Generated by javadoc (build 1.5.0_10) on Fri Jan 26 16:34:45 NZDT 2007 --><TITLE>MISMO</TITLE><META NAME="keywords" CONTENT="weka.classifiers.mi.MISMO class"><LINK REL ="stylesheet" TYPE="text/css" HREF="../../../stylesheet.css" TITLE="Style"><SCRIPT type="text/javascript">function windowTitle(){ parent.document.title="MISMO";}</SCRIPT><NOSCRIPT></NOSCRIPT></HEAD><BODY BGCOLOR="white" onload="windowTitle();"><!-- ========= START OF TOP NAVBAR ======= --><A NAME="navbar_top"><!-- --></A><A HREF="#skip-navbar_top" title="Skip navigation links"></A><TABLE BORDER="0" WIDTH="100%" CELLPADDING="1" CELLSPACING="0" SUMMARY=""><TR><TD COLSPAN=2 BGCOLOR="#EEEEFF" CLASS="NavBarCell1"><A NAME="navbar_top_firstrow"><!-- --></A><TABLE BORDER="0" CELLPADDING="0" CELLSPACING="3" SUMMARY=""> <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> <TD BGCOLOR="#EEEEFF" CLASS="NavBarCell1"> <A HREF="http://www.cs.waikato.ac.nz/ml/weka/" target="_blank"><FONT CLASS="NavBarFont1"><B>Weka's home</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/mi/MIOptimalBall.html" title="class in weka.classifiers.mi"><B>PREV CLASS</B></A> <A HREF="../../../weka/classifiers/mi/MISVM.html" title="class in weka.classifiers.mi"><B>NEXT CLASS</B></A></FONT></TD><TD BGCOLOR="white" CLASS="NavBarCell2"><FONT SIZE="-2"> <A HREF="../../../index.html?weka/classifiers/mi/MISMO.html" target="_top"><B>FRAMES</B></A> <A HREF="MISMO.html" target="_top"><B>NO FRAMES</B></A> <SCRIPT type="text/javascript"> <!-- if(window==top) { document.writeln('<A HREF="../../../allclasses-noframe.html"><B>All Classes</B></A>'); } //--></SCRIPT><NOSCRIPT> <A HREF="../../../allclasses-noframe.html"><B>All Classes</B></A></NOSCRIPT></FONT></TD></TR><TR><TD VALIGN="top" CLASS="NavBarCell3"><FONT SIZE="-2"> SUMMARY: NESTED | <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><A NAME="skip-navbar_top"></A><!-- ========= END OF TOP NAVBAR ========= --><HR><!-- ======== START OF CLASS DATA ======== --><H2><FONT SIZE="-1">weka.classifiers.mi</FONT><BR>Class MISMO</H2><PRE>java.lang.Object <IMG SRC="../../../resources/inherit.gif" ALT="extended by "><A HREF="../../../weka/classifiers/Classifier.html" title="class in weka.classifiers">weka.classifiers.Classifier</A> <IMG SRC="../../../resources/inherit.gif" ALT="extended by "><B>weka.classifiers.mi.MISMO</B></PRE><DL><DT><B>All Implemented Interfaces:</B> <DD>java.io.Serializable, java.lang.Cloneable, <A HREF="../../../weka/core/CapabilitiesHandler.html" title="interface in weka.core">CapabilitiesHandler</A>, <A HREF="../../../weka/core/MultiInstanceCapabilitiesHandler.html" title="interface in weka.core">MultiInstanceCapabilitiesHandler</A>, <A HREF="../../../weka/core/OptionHandler.html" title="interface in weka.core">OptionHandler</A>, <A HREF="../../../weka/core/TechnicalInformationHandler.html" title="interface in weka.core">TechnicalInformationHandler</A>, <A HREF="../../../weka/core/WeightedInstancesHandler.html" title="interface in weka.core">WeightedInstancesHandler</A></DD></DL><HR><DL><DT><PRE>public class <B>MISMO</B><DT>extends <A HREF="../../../weka/classifiers/Classifier.html" title="class in weka.classifiers">Classifier</A><DT>implements <A HREF="../../../weka/core/WeightedInstancesHandler.html" title="interface in weka.core">WeightedInstancesHandler</A>, <A HREF="../../../weka/core/MultiInstanceCapabilitiesHandler.html" title="interface in weka.core">MultiInstanceCapabilitiesHandler</A>, <A HREF="../../../weka/core/TechnicalInformationHandler.html" title="interface in weka.core">TechnicalInformationHandler</A></DL></PRE><P><!-- globalinfo-start --> Implements John Platt's sequential minimal optimization algorithm for training a support vector classifier.<br/> <br/> This implementation globally replaces all missing values and transforms nominal attributes into binary ones. It also normalizes all attributes by default. (In that case the coefficients in the output are based on the normalized data, not the original data --- this is important for interpreting the classifier.)<br/> <br/> Multi-class problems are solved using pairwise classification.<br/> <br/> To obtain proper probability estimates, use the option that fits logistic regression models to the outputs of the support vector machine. In the multi-class case the predicted probabilities are coupled using Hastie and Tibshirani's pairwise coupling method.<br/> <br/> Note: for improved speed normalization should be turned off when operating on SparseInstances.<br/> <br/> For more information on the SMO algorithm, see<br/> <br/> J. Platt: Machines using Sequential Minimal Optimization. In B. Schoelkopf and C. Burges and A. Smola, editors, Advances in Kernel Methods - Support Vector Learning, 1998.<br/> <br/> S.S. Keerthi, S.K. Shevade, C. Bhattacharyya, K.R.K. Murthy (2001). Improvements to Platt's SMO Algorithm for SVM Classifier Design. Neural Computation. 13(3):637-649. <p/> <!-- globalinfo-end --> <!-- technical-bibtex-start --> BibTeX: <pre> @incollection{Platt1998, author = {J. Platt}, booktitle = {Advances in Kernel Methods - Support Vector Learning}, editor = {B. Schoelkopf and C. Burges and A. Smola}, publisher = {MIT Press}, title = {Machines using Sequential Minimal Optimization}, year = {1998} } @article{Keerthi2001, author = {S.S. Keerthi and S.K. Shevade and C. Bhattacharyya and K.R.K. Murthy}, journal = {Neural Computation}, number = {3}, pages = {637-649}, title = {Improvements to Platt's SMO Algorithm for SVM Classifier Design}, volume = {13}, year = {2001} } </pre> <p/> <!-- technical-bibtex-end --> <!-- options-start --> Valid options are: <p/> <pre> -D If set, classifier is run in debug mode and may output additional info to the console</pre> <pre> -no-checks Turns off all checks - use with caution! Turning them off assumes that data is purely numeric, doesn't contain any missing values, and has a nominal class. Turning them off also means that no header information will be stored if the machine is linear. Finally, it also assumes that no instance has a weight equal to 0. (default: checks on)</pre> <pre> -C <double> The complexity constant C. (default 1)</pre> <pre> -N Whether to 0=normalize/1=standardize/2=neither. (default 0=normalize)</pre> <pre> -I Use MIminimax feature space. </pre> <pre> -L <double> The tolerance parameter. (default 1.0e-3)</pre> <pre> -P <double> The epsilon for round-off error. (default 1.0e-12)</pre> <pre> -M Fit logistic models to SVM outputs. </pre> <pre> -V <double> The number of folds for the internal cross-validation. (default -1, use training data)</pre> <pre> -W <double> The random number seed. (default 1)</pre> <pre> -K <classname and parameters> The Kernel to use. (default: weka.classifiers.functions.supportVector.PolyKernel)</pre> <pre> Options specific to kernel weka.classifiers.mi.supportVector.MIPolyKernel: </pre> <pre> -D Enables debugging output (if available) to be printed. (default: off)</pre> <pre> -no-checks Turns off all checks - use with caution! (default: checks on)</pre> <pre> -C <num> The size of the cache (a prime number). (default: 250007)</pre> <pre> -E <num> The Exponent to use. (default: 1.0)</pre> <pre> -L Use lower-order terms. (default: no)</pre> <!-- options-end --><P><P><DL><DT><B>Version:</B></DT> <DD>$Revision: 1.4 $</DD><DT><B>Author:</B></DT> <DD>Eibe Frank (eibe@cs.waikato.ac.nz), Shane Legg (shane@intelligenesis.net) (sparse vector code), Stuart Inglis (stuart@reeltwo.com) (sparse vector code), Lin Dong (ld21@cs.waikato.ac.nz) (code for adapting to MI data)</DD><DT><B>See Also:</B><DD><A HREF="../../../serialized-form.html#weka.classifiers.mi.MISMO">Serialized Form</A></DL><HR><P><!-- =========== FIELD SUMMARY =========== --><A NAME="field_summary"><!-- --></A><TABLE BORDER="1" WIDTH="100%" CELLPADDING="3" CELLSPACING="0" SUMMARY=""><TR BGCOLOR="#CCCCFF" CLASS="TableHeadingColor"><TH ALIGN="left" COLSPAN="2"><FONT SIZE="+2"><B>Field Summary</B></FONT></TH></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>static int</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/mi/MISMO.html#FILTER_NONE">FILTER_NONE</A></B></CODE><BR> No normalization/standardization</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>static int</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/mi/MISMO.html#FILTER_NORMALIZE">FILTER_NORMALIZE</A></B></CODE><BR> Normalize training data</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>static int</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/mi/MISMO.html#FILTER_STANDARDIZE">FILTER_STANDARDIZE</A></B></CODE><BR> Standardize training data</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE>static <A HREF="../../../weka/core/Tag.html" title="class in weka.core">Tag</A>[]</CODE></FONT></TD><TD><CODE><B><A HREF="../../../weka/classifiers/mi/MISMO.html#TAGS_FILTER">TAGS_FILTER</A></B></CODE><BR> The filter to apply to the training data</TD></TR></TABLE> <!-- ======== CONSTRUCTOR SUMMARY ======== --><A NAME="constructor_summary"><!-- --></A><TABLE BORDER="1" WIDTH="100%" CELLPADDING="3" CELLSPACING="0" SUMMARY=""><TR BGCOLOR="#CCCCFF" CLASS="TableHeadingColor"><TH ALIGN="left" COLSPAN="2"><FONT SIZE="+2"><B>Constructor Summary</B></FONT></TH></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><CODE><B><A HREF="../../../weka/classifiers/mi/MISMO.html#MISMO()">MISMO</A></B>()</CODE><BR> </TD></TR></TABLE> <!-- ========== METHOD SUMMARY =========== --><A NAME="method_summary"><!-- --></A><TABLE BORDER="1" WIDTH="100%" CELLPADDING="3" CELLSPACING="0" SUMMARY=""><TR BGCOLOR="#CCCCFF" CLASS="TableHeadingColor"><TH ALIGN="left" COLSPAN="2"><FONT SIZE="+2"><B>Method Summary</B></FONT></TH></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/mi/MISMO.html#attributeNames()">attributeNames</A></B>()</CODE><BR> Returns the attribute names.</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/mi/MISMO.html#bias()">bias</A></B>()</CODE><BR> Returns the bias of each binary SMO.</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/mi/MISMO.html#buildClassifier(weka.core.Instances)">buildClassifier</A></B>(<A HREF="../../../weka/core/Instances.html" title="class in weka.core">Instances</A> insts)</CODE><BR> Method for building the classifier.</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/mi/MISMO.html#buildLogisticModelsTipText()">buildLogisticModelsTipText</A></B>()</CODE><BR> Returns the tip text for this property</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/mi/MISMO.html#checksTurnedOffTipText()">checksTurnedOffTipText</A></B>()</CODE><BR> Returns the tip text for this property</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/mi/MISMO.html#classAttributeNames()">classAttributeNames</A></B>()</CODE><BR> Returns the names of the class attributes.</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/mi/MISMO.html#cTipText()">cTipText</A></B>()</CODE><BR> Returns the tip text for this property</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/mi/MISMO.html#distributionForInstance(weka.core.Instance)">distributionForInstance</A></B>(<A HREF="../../../weka/core/Instance.html" title="class in weka.core">Instance</A> inst)</CODE><BR> Estimates class probabilities for given instance.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor">⌨️ 快捷键说明
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