skglm.datafits.Quadratic#

class skglm.datafits.Quadratic[source]#

Quadratic datafit.

The datafit reads:

`1 / (2 xx n_"samples") ||y - Xw||_2 ^ 2`
Attributes:
Xtyarray, shape (n_features,)

Pre-computed quantity used during the gradient evaluation. Equal to X.T @ y.

__init__()[source]#

Methods

__init__()

full_grad_sparse(X_data, X_indptr, ...)

get_global_lipschitz(X, y)

get_global_lipschitz_sparse(X_data, ...)

get_lipschitz(X, y)

get_lipschitz_sparse(X_data, X_indptr, ...)

get_spec()

Specify the numba types of the class attributes.

gradient_scalar(X, y, w, Xw, j)

gradient_scalar_sparse(X_data, X_indptr, ...)

initialize(X, y)

Pre-computations before fitting on X and y.

initialize_sparse(X_data, X_indptr, X_indices, y)

Pre-computations before fitting on X and y when X is a sparse matrix.

intercept_update_step(y, Xw)

params_to_dict()

Get the parameters to initialize an instance of the class.

value(y, w, Xw)

Value of datafit at vector w.