secure_learning.models.secure_ridge module

Implementation of Ridge regression model.

class secure_learning.models.secure_ridge.Ridge(solver_type=SolverTypes.GD, alpha=1)[source]

Bases: Linear

Solver for Ridge regression. Optimizes a model with objective function

\[\frac{1}{{2n}_{\textrm{samples}}} \times ||y - Xw||^2_2 + \frac{\alpha}{2} \times ||w||^2_2\]

__init__(solver_type=SolverTypes.GD, alpha=1)[source]

Constructor method.

Parameters:

solver_type (SolverTypes) – Solver type to use (e.g. Gradient Descent aka GD)
alpha (float) – Regularization parameter