OptimalLinearRegression

class menpofit.math.OptimalLinearRegression(variance=None, bias=True)

Bases: object

Class for training and applying Multivariate Linear Regression using optimal reconstructions.

Parameters:

• variance (float or None, optional) – The SVD variance.
• bias (bool, optional) – If True, a bias term is used.

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.