chemometrics.mcr.regressor.NNLS¶
- class chemometrics.mcr.regressor.NNLS(*args, **kwargs)¶
Bases:
chemometrics.mcr._regressor.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_
isX.T
, which is the formalism of scikit-learn- __init__(*args, **kwargs)¶
Methods
__init__
(*args, **kwargs)fit
(A, B)Solve for X: AX = B
Attributes
- fit(A, B)¶
Solve for X: AX = B