C# Class numl.Supervised.Regression.LogisticRegressionModel

A Logistic Regression Model object
Inheritance: Model, IClassifier
Afficher le fichier Open project: sethjuarez/numl Class Usage Examples

Méthodes publiques

Méthode Description
IncreaseDimensions ( Vector x, int polynomialFeatures ) : Vector

Adds a specified number of polynomial features to the training / test Vector.
LogisticRegressionModel ( ) : System

Default constructor
Predict ( Vector x ) : double

Create a prediction based on the learned Theta values and the supplied test item.
PredictRaw ( Vector x ) : double

Computes the probability of the prediction being True.

Method Details

IncreaseDimensions() public static méthode

Adds a specified number of polynomial features to the training / test Vector.
public static IncreaseDimensions ( Vector x, int polynomialFeatures ) : Vector
x numl.Math.LinearAlgebra.Vector Training / Testing record
polynomialFeatures int Number of polynomial features to add
Résultat numl.Math.LinearAlgebra.Vector

LogisticRegressionModel() public méthode

Default constructor
public LogisticRegressionModel ( ) : System
Résultat System

Predict() public méthode

Create a prediction based on the learned Theta values and the supplied test item.
public Predict ( Vector x ) : double
x numl.Math.LinearAlgebra.Vector Training record
Résultat double

PredictRaw() public méthode

Computes the probability of the prediction being True.
public PredictRaw ( Vector x ) : double
x numl.Math.LinearAlgebra.Vector
Résultat double