SparseGroupLasso

class superglm.SparseGroupLasso(

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

alpha: float = 0.5,

flavor: Flavor | None = None,

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

)

Bases: object

Sparse group lasso: lambda1 * [(1-alpha) * group_L2 + alpha * L1].

Parameters:

lambda1float, {“auto”}, or None

Regularisation strength. None disables selection and "auto" explicitly requests automatic calibration.

alphafloat

Mixing parameter in [0, 1]. 0 = pure group lasso, 1 = pure L1.

flavorFlavor or None

Optional modifier (e.g. Adaptive).

prox_group(

bg: NDArray,

group: GroupSlice,

step: float,

) → NDArray

L1 soft-threshold then group L2 prox for a single group.

prox(

beta: NDArray,

groups: list[GroupSlice],

step: float,

) → NDArray

Proximal operator via decomposition: L1 soft-threshold then group L2 prox.

eval(

beta: NDArray,

groups: list[GroupSlice],

) → float

Penalty value.