Objeck Documentation

LinearRegression

Simple linear regression using least squares. Fits y = X * coefficients via the normal equation.

Fits the model to training data using least squares.

method : public : Fit(X:Float[,], y:Float[,]) ~ Bool

Parameters

Name	Type	Description
X	Float	feature matrix (rows=samples, cols=features)
y	Float	target matrix (rows=samples, cols=1)

Return

Type	Description
Bool	true if fitting succeeded

Gets the computed coefficients.

method : public : GetCoefficients() ~ Float[]

Return

Type	Description
Float	coefficient array, or Nil if not fitted

Gets the R-squared goodness of fit.

method : public : GetRSquared() ~ Float

Return

Type	Description
Float	R-squared value

Whether the model has been fitted.

method : public : IsFitted() ~ Bool

Return

Type	Description
Bool	true if fitted

Constructor

New()

Predicts target values for new input data.

method : public : Predict(X:Float[,]) ~ Float[,]

Parameters

Name	Type	Description
X	Float	feature matrix

Return

Type	Description
Float	prediction matrix, or Nil if not fitted