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<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 optimizationmethods, e.g. evolutionary strategies or particle swarm optimization. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.operator.learner.functions.kernel.functions"><B>com.rapidminer.operator.learner.functions.kernel.functions</B></A></TD><TD>This package contains some common kernel functions. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.operator.learner.functions.kernel.hyperhyper"><B>com.rapidminer.operator.learner.functions.kernel.hyperhyper</B></A></TD><TD>This package contains classes for the HyperHyper learner. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.operator.learner.functions.kernel.jmysvm.svm"><B>com.rapidminer.operator.learner.functions.kernel.jmysvm.svm</B></A></TD><TD>The main package for the Java version of the the regression and classification support vector machine mySVM. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.operator.learner.functions.kernel.logistic"><B>com.rapidminer.operator.learner.functions.kernel.logistic</B></A></TD><TD>The main package for Kernel Logistic Regression (KLR). </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.operator.learner.functions.neuralnet"><B>com.rapidminer.operator.learner.functions.neuralnet</B></A></TD><TD>This package contains a neural net learner based on Joone. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.operator.learner.igss"><B>com.rapidminer.operator.learner.igss</B></A></TD><TD>Provides classes for learning operator Iterating Generic Sequential Sampling. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.operator.learner.lazy"><B>com.rapidminer.operator.learner.lazy</B></A></TD><TD>Learning schemes which perform lazy learning. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.operator.learner.meta"><B>com.rapidminer.operator.learner.meta</B></A></TD><TD>Meta learning schemes which uses other learning operators to increase the performance. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.operator.learner.rules"><B>com.rapidminer.operator.learner.rules</B></A></TD><TD>Provides rule learners. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.operator.learner.tree"><B>com.rapidminer.operator.learner.tree</B></A></TD><TD>Provides decision tree learners. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.operator.learner.weka"><B>com.rapidminer.operator.learner.weka</B></A></TD><TD>Operators which encapsulate the learning schemes provided by Weka. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.operator.meta"><B>com.rapidminer.operator.meta</B></A></TD><TD>Provides operators for experiment iteration, meta operators, and optimization. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.operator.meta.branch"><B>com.rapidminer.operator.meta.branch</B></A></TD><TD>Provides operators for conditioned branching. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.operator.olap"><B>com.rapidminer.operator.olap</B></A></TD><TD>This package contains some simple operators for basic OLAP analysis like grouping and aggregation. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.operator.olap.aggregation"><B>com.rapidminer.operator.olap.aggregation</B></A></TD><TD>This package contains some aggregation functions which can be used by OLAP processing. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.operator.performance"><B>com.rapidminer.operator.performance</B></A></TD><TD>Provides performance evaluating operators and performance criteria. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.operator.performance.cost"><B>com.rapidminer.operator.performance.cost</B></A></TD><TD>This package contains cost-based performance evaluations. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.operator.postprocessing"><B>com.rapidminer.operator.postprocessing</B></A></TD><TD>Operators for post processing, usually used for models. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.operator.preprocessing"><B>com.rapidminer.operator.preprocessing</B></A></TD><TD>Operators for preprocessing purposes. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.operator.preprocessing.discretization"><B>com.rapidminer.operator.preprocessing.discretization</B></A></TD><TD>Contains discretization operators which can be used to transform numerical into nominal attributes. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.operator.preprocessing.filter"><B>com.rapidminer.operator.preprocessing.filter</B></A></TD><TD>Containing filter operators changing the input example set, e.g. by removing certain attributes or changing the data. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.operator.preprocessing.filter.attributes"><B>com.rapidminer.operator.preprocessing.filter.attributes</B></A></TD><TD>This package contains the attribute filter. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.operator.preprocessing.normalization"><B>com.rapidminer.operator.preprocessing.normalization</B></A></TD><TD>Preprocessing operators used for normalization. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.operator.preprocessing.outlier"><B>com.rapidminer.operator.preprocessing.outlier</B></A></TD><TD>Operators for outlier detection. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.operator.preprocessing.sampling"><B>com.rapidminer.operator.preprocessing.sampling</B></A></TD><TD>Preprocessing operators used for sampling. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.operator.preprocessing.weighting"><B>com.rapidminer.operator.preprocessing.weighting</B></A></TD><TD>This package methods for the weighting of examples. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.operator.similarity"><B>com.rapidminer.operator.similarity</B></A></TD><TD>Basic framework for similarities. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.operator.similarity.clustermodel"><B>com.rapidminer.operator.similarity.clustermodel</B></A></TD><TD>Similarity induced by cluster models and cluster model similarity. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.operator.validation"><B>com.rapidminer.operator.validation</B></A></TD><TD>Operators for estimation of the performance which can be achieved by learning schemes (and other predictive operators). </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.operator.validation.clustering"><B>com.rapidminer.operator.validation.clustering</B></A></TD><TD>Evaluation methods for clustering. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.operator.validation.clustering.itemdistribution"><B>com.rapidminer.operator.validation.clustering.itemdistribution</B></A></TD><TD>Contains classes for evaluating the distribution of items among clusters. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.operator.validation.significance"><B>com.rapidminer.operator.validation.significance</B></A></TD><TD>Statistical significance like ANOVA or t-tests. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.operator.visualization"><B>com.rapidminer.operator.visualization</B></A></TD><TD>The operators in this package might be useful for visualization purposes. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.parameter.conditions"><B>com.rapidminer.parameter.conditions</B></A></TD><TD>This package contains conditions for ParameterTypes. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.parameter.value"><B>com.rapidminer.parameter.value</B></A></TD><TD>This package contains helper classes for defining different types of parameter values, for example for parameter optimization operators. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.tools"><B>com.rapidminer.tools</B></A></TD><TD>Provides tools for RapidMiner like parsers for the input files. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.tools.math.matrix"><B>com.rapidminer.tools.math.matrix</B></A></TD><TD>Utitility classes for matrices. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.tools.math.similarity"><B>com.rapidminer.tools.math.similarity</B></A></TD><TD>This package consists similariy and distance measures. </TD></TR></TABLE> <P><A NAME="com.rapidminer"><!-- --></A><TABLE BORDER="1" WIDTH="100%" CELLPADDING="3" CELLSPACING="0" SUMMARY=""><TR BGCOLOR="#CCCCFF" CLASS="TableHeadingColor"><TH ALIGN="left" COLSPAN="2"><FONT SIZE="+2">Uses of <A HREF="../../../../com/rapidminer/operator/Operator.html" title="class in com.rapidminer.operator">Operator</A> in <A HREF="../../../../com/rapidminer/package-summary.html">com.rapidminer</A></FONT></TH></TR></TABLE> <P><TABLE BORDER="1" WIDTH="100%" CELLPADDING="3" CELLSPACING="0" SUMMARY=""><TR BGCOLOR="#CCCCFF" CLASS="TableSubHeadingColor"><TH ALIGN="left" COLSPAN="2">Methods in <A HREF="../../../../com/rapidminer/package-summary.html">com.rapidminer</A> that return <A HREF="../../../../com/rapidminer/operator/Operator.html" title="class in com.rapidminer.operator">Operator</A></FONT></TH></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> <A HREF="../../../../com/rapidminer/operator/Operator.html" title="class in com.rapidminer.operator">Operator</A></CODE></FONT></TD><TD><CODE><B>Process.</B><B><A HREF="../../../../com/rapidminer/Process.html#getCurrentOperator()">getCurrentOperator</A></B>()</CODE><BR> Returns the operator that is currently being executed.</TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> <A HREF="../../../../com/rapidminer/operator/Operator.html" title="class in com.rapidminer.operator">Operator</A></CODE></FONT></TD><TD><CODE><B>Process.</B><B><A HREF="../../../../com/rapidminer/Process.html#getOperator(java.lang.String)">getOperator</A></B>(java.lang.String name)</CODE><BR> Returns the operator with the given name.</TD></TR></TABLE> <P><TABLE BORDER="1" WIDTH="100%" CELLPADDING="3" CELLSPACING="0" SUMMARY=""><TR BGCOLOR="#CCCCFF" CLASS="TableSubHeadingColor"><TH ALIGN="left" COLSPAN="2">Methods in <A HREF="../../../../com/rapidminer/package-summary.html">com.rapidminer</A> that return types with arguments of type <A HREF="../../../../com/rapidminer/operator/Operator.html" title="class in com.rapidminer.operator">Operator</A></FONT></TH></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD ALIGN="right" VALIGN="top" WIDTH="1%"><FONT SIZE="-1"><CODE> java.util.Collection<<A HREF="../../../../com/rapidminer/operator/Operator.html" title="class in com.rapidminer.operator">Operator</A>></CODE></FONT></TD><TD><CODE><B>Process.</B><B><A HREF="../../../../com/rapidminer/Process.html#getAllOperators()">getAllOperators</A></B>()</CODE><BR>
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