|class||DecisionTree< FitnessFunction, NumericSplitType, CategoricalSplitType, DimensionSelectionType, ElemType, NoRecursion >|
|This class implements a generic decision tree learner. More...|
Linear algebra utility functions, generally performed on matrices or vectors.
Trees and tree-building procedures.
|using||DecisionStump = DecisionTree< FitnessFunction, NumericSplitType, CategoricalSplitType, DimensionSelectType, ElemType, false >|
|Convenience typedef for decision stumps (single level decision trees). More...|
|typedef DecisionTree< InformationGain, BestBinaryNumericSplit, AllCategoricalSplit, AllDimensionSelect, double, true >||ID3DecisionStump|
|Convenience typedef for ID3 decision stumps (single level decision trees made with the ID3 algorithm). More...|
A generic decision tree learner. Its behavior can be controlled via template arguments.
mlpack is free software; you may redistribute it and/or modify it under the terms of the 3-clause BSD license. You should have received a copy of the 3-clause BSD license along with mlpack. If not, see http://www.opensource.org/licenses/BSD-3-Clause for more information.
Definition in file decision_tree.hpp.