C# Class MyMediaLite.Classification.LogisticRegression

Regularized logistic regression trained by stochastic gradient descent

Implementation for dense feature vectors. Predictor variables are implemented transposed to their normal layout, due to being used in for the KDD Cup 2011 ensembles.

Afficher le fichier Open project: zenogantner/MML-KDD Class Usage Examples

Méthodes publiques

Свойство	Type	Description
parameters	IList

Méthodes publiques

Méthode	Description
InitModel ( ) : void
LogisticRegression ( ) : System	Default constructor
PredictProbability ( IList input ) : double	Predict probability for given features
Train ( ) : void	Train using stochastic gradient descent

Method Details

InitModel() public méthode

public InitModel ( ) : void
Résultat	void

LogisticRegression() public méthode

Default constructor

public LogisticRegression ( ) : System
Résultat	System

PredictProbability() public méthode

Predict probability for given features

public PredictProbability ( IList input ) : double
input	IList	the input
Résultat	double

Train() public méthode

Train using stochastic gradient descent

public Train ( ) : void
Résultat	void

Property Details

parameters public_oe property

public IList parameters
Résultat	IList