`rlassomodels`.RlassoLogit¶

class rlassomodels.RlassoLogit(post=True, fit_intercept=True, c=1.1, gamma=0.05, zero_tol=0.0001, solver_opts=None)[source]¶

fit(X, y, *, gamma=None)[source]¶

Fit the model to the data.

Parameters

X: array-like, shape (n_samples, n_features): Design matrix.
y: array-like, shape (n_samples,): Target vector.
gamma: float, optional (default: 0.1 / np.log(n_samples))

Returns

self: object: Returns self.

predict(X)[source]¶: Predict the class labels for X.

predict_log_proba(X)[source]¶: Predict class log-probabilities for X.

predict_proba(X)[source]¶: Predict class probabilities for X.