C# Class Accord.MachineLearning.DecisionTrees.Rules.Simplification

Decision rule simplification algorithm.

Afficher le fichier Open project: accord-net/framework Class Usage Examples

Méthodes publiques

Méthode	Description
CanEliminate ( bool actual, bool expected ) : bool	Checks if two variables can be eliminated.
CanEliminate ( bool actual, bool expected, double alpha ) : bool	Checks if two variables can be eliminated.
Compute ( double inputs, int outputs ) : double	Computes the reduction algorithm.
ComputeError ( double inputs, int outputs ) : double	Computes the average decision error.
Simplification ( DecisionSet list ) : Accord.Math	Initializes a new instance of the Simplification class.

Private Methods

Méthode	Description
computeError ( double inputs, int outputs, IEnumerable rules ) : double
match ( IEnumerable rules, double input ) : double?

Method Details

CanEliminate() public méthode

Checks if two variables can be eliminated.

public CanEliminate ( bool actual, bool expected ) : bool
actual	bool
expected	bool
Résultat	bool

CanEliminate() public static méthode

Checks if two variables can be eliminated.

public static CanEliminate ( bool actual, bool expected, double alpha ) : bool
actual	bool
expected	bool
alpha	double
Résultat	bool

Compute() public méthode

Computes the reduction algorithm.

public Compute ( double inputs, int outputs ) : double
inputs	double	A set of training inputs.
outputs	int	The outputs corresponding to each of the inputs.
Résultat	double

ComputeError() public méthode

Computes the average decision error.

public ComputeError ( double inputs, int outputs ) : double
inputs	double	A set of input vectors.
outputs	int	A set of corresponding output vectors.
Résultat	double

Simplification() public méthode

Initializes a new instance of the Simplification class.

public Simplification ( DecisionSet list ) : Accord.Math
list	DecisionSet	The decision set to be simplified.
Résultat	Accord.Math