mcmodels.regressors.nonnegative_regression

mcmodels.regressors.nonnegative_regression(X, y, sample_weight=None)

Solve the nonnegative least squares estimate regression problem.

Solves \(\underset{x}{\text{argmin}} \| Ax - b \|_2^2\) subject to \(x \geq 0\) using scipy.optimize.nnls

Parameters:

X : array, shape = (n_samples, n_features)

Training data.

y : array, shape = (n_samples,) or (n_samples, n_targets)

Target values.

sample_weight : float or array-like, shape (n_samples,), optional (default = None)

Individual weights for each sample.

Returns:

coef : array, shape = (n_features,) or (n_samples, n_features)

Weight vector(s).

res : float

The residual, \(\| Ax - y \|_2\).