#include <mlpack/prereqs.hpp>
#include "gini_gain.hpp"
#include "information_gain.hpp"
#include "best_binary_numeric_split.hpp"
#include "random_binary_numeric_split.hpp"
#include "all_categorical_split.hpp"
#include "all_dimension_select.hpp"
#include <type_traits>
#include "decision_tree_impl.hpp"

Include dependency graph for decision_tree.hpp:

This graph shows which files directly or indirectly include this file:

Go to the source code of this file.

Classes
class	mlpack::tree::DecisionTree< FitnessFunction, NumericSplitType, CategoricalSplitType, DimensionSelectionType, NoRecursion >
	This class implements a generic decision tree learner. More...

Namespaces
	mlpack
	Linear algebra utility functions, generally performed on matrices or vectors.

	mlpack::tree
	Trees and tree-building procedures.

Typedefs
template<typename FitnessFunction = GiniGain, template< typename > class NumericSplitType = BestBinaryNumericSplit, template< typename > class CategoricalSplitType = AllCategoricalSplit, typename DimensionSelectType = AllDimensionSelect>
using	mlpack::tree::DecisionStump = DecisionTree< FitnessFunction, NumericSplitType, CategoricalSplitType, DimensionSelectType, false >
	Convenience typedef for decision stumps (single level decision trees).

typedef DecisionTree< InformationGain, BestBinaryNumericSplit, AllCategoricalSplit, AllDimensionSelect, true >	mlpack::tree::ID3DecisionStump
	Convenience typedef for ID3 decision stumps (single level decision trees made with the ID3 algorithm).

Detailed Description

Author: Ryan Curtin

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.

Classes

Namespaces

Typedefs

Detailed Description