"DecisionTree" (Machine Learning Method)

Details & Suboptions

  • A decision tree is a flow chartlike structure in which each internal node represents a "test" on a feature, each branch represents the outcome of the test, and each leaf represents a class or value distribution.
  • The following options can be given:
  • "DistributionSmoothing"1regularization parameter
    "FeatureFraction"1the fraction of features to be randomly selected for training

Examples

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Basic Examples  (2)

Train a predictor function on labeled examples:

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Look at the PredictorInformation:

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Predict a new example:

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Generate some data and visualize it:

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Train a predictor function on it:

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Compare the data with the predicted values and look at the standard deviation:

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Options  (4)

See Also

Classify  Predict  ClassifierFunction  PredictorFunction  ClassifierMeasurements  PredictorMeasurements  ClassifierInformation  PredictorInformation  SequencePredict  ClusterClassify

Related Demonstrations

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