OptimalLinearRegression

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

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)[source]

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)[source]

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)[source]

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.