skglm.penalties.SCAD

class skglm.penalties.SCAD(alpha, gamma)

Smoothly Clipped Absolute Deviation.

Notes

With `x >= 0`:

`"pen"(x) = { (alpha x , if \ \ \ \ \ \ \ \ \ \ x <= alpha), (2 alpha gamma x - x^2 - alpha^2 / 2 (gamma - 1) , if alpha \ \ < x <= alpha gamma), (alpha^2 (gamma + 1) / 2 , if alpha gamma < x ) :}`

`"value" = sum_(j=1)^(n_"features") "pen"(abs(w_j))`

__init__(alpha, gamma)

Methods

__init__(alpha, gamma)
generalized_support(w)	Return a mask with non-zero coefficients.
get_spec()	Specify the numba types of the class attributes.
is_penalized(n_features)	Return a binary mask with the penalized features.
params_to_dict()	Get the parameters to initialize an instance of the class.
prox_1d(value, stepsize, j)	Compute the proximal operator of SCAD penalty.
subdiff_distance(w, grad, ws)	Compute distance of negative gradient to the subdifferential at w.
value(w)	Compute the value of the SCAD penalty at w.