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
- name = 'Ridge regression'