GroupElasticNet

class superglm.GroupElasticNet(

lambda1: float | Literal['auto'] | None = None,

alpha: float = 0.5,

flavor: Flavor | None = None,

features: str | list[str] | None = None,

)

Bases: object

Group elastic net: lambda1 * [alpha * group_L2 + (1-alpha)/2 * L2^2].

alpha=1.0 → pure group lasso, alpha=0.0 → pure ridge.

Parameters:

lambda1float, {“auto”}, or None

Regularisation strength. None disables selection and "auto" explicitly requests calibration to 10% of lambda_max.

alphafloat

Mixing parameter in [0, 1]. 1 = pure group lasso, 0 = pure ridge.

flavorFlavor or None

Optional modifier (e.g. Adaptive) that adjusts group weights based on an initial estimate.

prox_group(

bg: NDArray,

group: GroupSlice,

step: float,

) → NDArray

Closed-form composite proximal operator for a single group.

prox(

beta: NDArray,

groups: list[GroupSlice],

step: float,

) → NDArray

Apply the closed-form group elastic-net prox to each group.

eval(

beta: NDArray,

groups: list[GroupSlice],

) → float

Penalty value: lambda1 * [alpha * group_L2 + (1-alpha)/2 * L2^2].