decision_tree.hpp File Reference
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Classes

class  DecisionTree< FitnessFunction, NumericSplitType, CategoricalSplitType, DimensionSelectionType, ElemType, 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
,
typename
ElemType
=
double
>
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...

 

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.

Definition in file decision_tree.hpp.