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java.lang.Objectcom.rapidminer.operator.Operator
com.rapidminer.operator.OperatorChain
com.rapidminer.operator.learner.meta.AbstractMetaLearner
com.rapidminer.operator.learner.tree.MultiwayDecisionTree
public class MultiwayDecisionTree
This operator is a meta learner for numerical tree builder. It might be used to flatten decision trees, which consists of many splits on the same attribute. All numerical attributes used for at least one decision in a tree will be discretized with the decisions' split points as borders. For example, if attribute att1 is splitted on the points 4.5 and 2.1 then it will be discretized in three values: -Infinity to 2.1, 2.1 to 4.5 and 4.5 to Infinity. After this, a new tree is grown on the transformed data. Since the used attributes are now numerical, all splits will be made immediately and hence the depth might be reduced. Please note: The resulting tree might be easier to comprehend, but this have to make it perform neither better nor worse! To get an impression of the reliability of the result perform a XValidation.
| Constructor Summary | |
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MultiwayDecisionTree(OperatorDescription description)
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| Method Summary | |
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Model |
learn(ExampleSet exampleSet)
Trains a model. |
| Methods inherited from class com.rapidminer.operator.learner.meta.AbstractMetaLearner |
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apply, applyInnerLearner, getEstimatedPerformance, getInnerOperatorCondition, getInputClasses, getInputDescription, getMaxNumberOfInnerOperators, getMinNumberOfInnerOperators, getOutputClasses, getWeights, shouldCalculateWeights, shouldEstimatePerformance, supportsCapability |
| Methods inherited from class java.lang.Object |
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clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait |
| Methods inherited from interface com.rapidminer.operator.learner.Learner |
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getName |
| Constructor Detail |
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public MultiwayDecisionTree(OperatorDescription description)
description - | Method Detail |
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public Model learn(ExampleSet exampleSet)
throws OperatorException
Learner
OperatorException
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