mlr_svd

menpo.fit.regression.regressionfunctions.mlr_svd(X, T, variance=None)[source]

Multivariate Linear Regression using SVD decomposition

Parameters:

X: numpy.array :

The regression features used to create the coefficient matrix.

T: numpy.array :

The shapes differential that denote the dependent variable.

variance: float or None, Optional :

The SVD variance.

Default: None

Returns:

mlr_svd_fitting: function/closure :

The closure of the regression method.

Raises:

ValueError :

variance must be set to a number between 0 and 1