chemometrics.mcr.regressor.NNLS

class chemometrics.mcr.regressor.NNLS(*args, **kwargs)

Bases: LinearRegression

Non-negative constrained least squares regression

AX = B, solve for X (coeffients.T)

coef_

Regression coefficients

Type

ndarray

residual_

Residual (sum-of-squares)

Type

ndarray

Notes

This is simply a wrapped version of NNLS (scipy.optimize.nnls).

coef_ is X.T, which is the formalism of scikit-learn

__init__(*args, **kwargs)

Methods

__init__(*args, **kwargs)
fit(A, B)	Solve for X: AX = B

Attributes

coef_

fit(A, B)

Solve for X: AX = B