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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_13) on Mon Jul 14 01:36:56 CEST 2008 --><TITLE>Uses of Interface com.rapidminer.example.ExampleSet (RapidMiner Class Documentation)</TITLE><LINK REL ="stylesheet" TYPE="text/css" HREF="../../../../stylesheet.css" TITLE="Style"><SCRIPT type="text/javascript">function windowTitle(){ parent.document.title="Uses of Interface com.rapidminer.example.ExampleSet (RapidMiner Class Documentation)";}</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" 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Interface<br>com.rapidminer.example.ExampleSet</B></H2></CENTER><TABLE BORDER="1" WIDTH="100%" CELLPADDING="3" CELLSPACING="0" SUMMARY=""><TR BGCOLOR="#CCCCFF" CLASS="TableHeadingColor"><TH ALIGN="left" COLSPAN="2"><FONT SIZE="+2">Packages that use <A HREF="../../../../com/rapidminer/example/ExampleSet.html" title="interface in com.rapidminer.example">ExampleSet</A></FONT></TH></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.datatable"><B>com.rapidminer.datatable</B></A></TD><TD>DataTables are the most important data container interface for RapidMiner which are used for all statistics and plotting purposes. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.example"><B>com.rapidminer.example</B></A></TD><TD>The data core classes of RapidMiner. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.example.set"><B>com.rapidminer.example.set</B></A></TD><TD>The available views (example sets) on the example tables. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.example.table"><B>com.rapidminer.example.table</B></A></TD><TD>The available example table implementations (data sources). </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.example.test"><B>com.rapidminer.example.test</B></A></TD><TD>Test classes for classes in the example package. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.generator"><B>com.rapidminer.generator</B></A></TD><TD>Provides feature generators. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.gui"><B>com.rapidminer.gui</B></A></TD><TD>Provides the main GUI classes. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.gui.viewer"><B>com.rapidminer.gui.viewer</B></A></TD><TD>This package contain viewer classes for some standard data types like ExampleSets, DataTables etc. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.operator"><B>com.rapidminer.operator</B></A></TD><TD>Provides operators for machine learning and data pre-processing. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.operator.features"><B>com.rapidminer.operator.features</B></A></TD><TD>Provides feature handling operators. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.operator.features.aggregation"><B>com.rapidminer.operator.features.aggregation</B></A></TD><TD>Provides operators for automatic feature aggregation. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.operator.features.construction"><B>com.rapidminer.operator.features.construction</B></A></TD><TD>Provides operators for automatic feature construction. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.operator.features.selection"><B>com.rapidminer.operator.features.selection</B></A></TD><TD>Provides operators for automatic feature selection. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.operator.features.transformation"><B>com.rapidminer.operator.features.transformation</B></A></TD><TD>Provides operators for feature space transformations like PCA or ICA. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.operator.features.weighting"><B>com.rapidminer.operator.features.weighting</B></A></TD><TD>Operators to weight features or determine feature relevance. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.operator.io"><B>com.rapidminer.operator.io</B></A></TD><TD>Operators to read data from files or write them into files. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.operator.learner"><B>com.rapidminer.operator.learner</B></A></TD><TD>Provides learning operators. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.operator.learner.bayes"><B>com.rapidminer.operator.learner.bayes</B></A></TD><TD>This package contains classes and operators for Naive Bayes learning. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.operator.learner.clustering"><B>com.rapidminer.operator.learner.clustering</B></A></TD><TD>Core data structures for the clustering plugin. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.operator.learner.clustering.characterization"><B>com.rapidminer.operator.learner.clustering.characterization</B></A></TD><TD>This package contain some possible cluster characterizations, e.g. based on simple models like OneR. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.operator.learner.clustering.clusterer"><B>com.rapidminer.operator.learner.clustering.clusterer</B></A></TD><TD>Clustering algorithms. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.operator.learner.clustering.constrained"><B>com.rapidminer.operator.learner.clustering.constrained</B></A></TD><TD>Provides constrained and semisupervised clustering schemes. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.operator.learner.clustering.hierarchical"><B>com.rapidminer.operator.learner.clustering.hierarchical</B></A></TD><TD>Methods and framework for hierarchical clustering. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.operator.learner.clustering.hierarchical.upgma"><B>com.rapidminer.operator.learner.clustering.hierarchical.upgma</B></A></TD><TD>UPGMA Clustering. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.operator.learner.functions"><B>com.rapidminer.operator.learner.functions</B></A></TD><TD>This package contains learners based on the conceptof function approximation. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.operator.learner.functions.kernel"><B>com.rapidminer.operator.learner.functions.kernel</B></A></TD><TD>Learning schemes which make use of kernel functions to transform the feature space, e.g. support vector machines. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.operator.learner.functions.kernel.evosvm"><B>com.rapidminer.operator.learner.functions.kernel.evosvm</B></A></TD><TD>Implementations of SVMs which makes use of general purpose optimization⌨️ 快捷键说明
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