skglm.penalties.IndicatorBox

class skglm.penalties.IndicatorBox(alpha)

Box constraint penalty.

Notes

`bb"1"_([0, alpha]^(n_"samples"))`

where `bb"1"` is the indicator function of the convex set `[0, alpha]^(n_"samples")`

__init__(alpha)

Methods

__init__(alpha)
generalized_support(w)	Return a mask with coefficients that are neither 0 nor alpha.
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 the Indicator Box (box projection).
subdiff_distance(w, grad, ws)	Compute distance of negative gradient to the subdifferential at w.
value(w)	Compute the value of the IndicatorBox at w.