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Interface<br>com.rapidminer.tools.LoggingHandler</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/tools/LoggingHandler.html" title="interface in com.rapidminer.tools">LoggingHandler</A></FONT></TH></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.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.generator"><B>com.rapidminer.operator.generator</B></A></TD><TD>Provides operators for data generation. </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.associations"><B>com.rapidminer.operator.learner.associations</B></A></TD><TD>This package contains classes and operators for association rule mining and frequent item set mining. </TD></TR><TR BGCOLOR="white" CLASS="TableRowColor"><TD><A HREF="#com.rapidminer.operator.learner.associations.fpgrowth"><B>com.rapidminer.operator.learner.associations.fpgrowth</B></A></TD><TD>This package contains classes and operators for association rule mining and frequent item set mining based on FPGrowth. </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.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.constrained.constraints"><B>com.rapidminer.operator.learner.clustering.constrained.constraints</B></A></TD><TD>Provides helper classes for handling the constraints in 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 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.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.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.igss.hypothesis"><B>com.rapidminer.operator.learner.igss.hypothesis</B></A></TD><TD>Provides the hypothesis 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>⌨️ 快捷键说明
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