IRLRegression

class menpofit.math.IRLRegression(alpha=0, bias=True, incrementable=False)

Bases: object

Class for training and applying Incremental Regularized Linear Regression.

Parameters:

• alpha (float, optional) – The regularization parameter of the features.
• bias (bool, optional) – If True, a bias term is used.
• incrementable (bool, optional) – If True, then the regression model will have the ability to get incremented.

increment(X, Y)

Incrementally update the regression model.

Parameters:

• X ((n_features, n_samples) ndarray) – The array of feature vectors.
• Y ((n_dims, n_samples) ndarray) – The array of target vectors.

Raises:

ValueError – Model is not incrementable

predict(x)

Makes a prediction using the trained regression model.

Parameters:x ((n_features,) ndarray) – The input feature vector. Returns:prediction ((n_dims,) ndarray) – The prediction vector.

train(X, Y)

Train the regression model.

Parameters:

• X ((n_features, n_samples) ndarray) – The array of feature vectors.
• Y ((n_dims, n_samples) ndarray) – The array of target vectors.