linear_model.RidgeClassifier()

class sklearn.linear_model.RidgeClassifier(alpha=1.0, fit_intercept=True, normalize=False, copy_X=True, max_iter=None, tol=0.001

2017-01-15 04:23:46
linear_model.SGDRegressor()

class sklearn.linear_model.SGDRegressor(loss='squared_loss', penalty='l2', alpha=0.0001, l1_ratio=0.15, fit_intercept=True, n_iter=5

2017-01-15 04:23:50
linear_model.MultiTaskElasticNetCV()

class sklearn.linear_model.MultiTaskElasticNetCV(l1_ratio=0.5, eps=0.001, n_alphas=100, alphas=None, fit_intercept=True

2017-01-15 04:23:33
linear_model.HuberRegressor()

class sklearn.linear_model.HuberRegressor(epsilon=1.35, max_iter=100, alpha=0.0001, warm_start=False, fit_intercept=True, tol=1e-05)

2017-01-15 04:23:19
linear_model.Ridge()

class sklearn.linear_model.Ridge(alpha=1.0, fit_intercept=True, normalize=False, copy_X=True, max_iter=None, tol=0.001, solver='auto',

2017-01-15 04:23:45
sklearn.linear_model.lasso_path()

sklearn.linear_model.lasso_path(X, y, eps=0.001, n_alphas=100, alphas=None, precompute='auto', Xy=None, copy_X=True, coef_init=None

2017-01-15 04:26:11
linear_model.OrthogonalMatchingPursuit()

class sklearn.linear_model.OrthogonalMatchingPursuit(n_nonzero_coefs=None, tol=None, fit_intercept=True, normalize=True

2017-01-15 04:23:36
linear_model.ElasticNetCV()

class sklearn.linear_model.ElasticNetCV(l1_ratio=0.5, eps=0.001, n_alphas=100, alphas=None, fit_intercept=True, normalize=False,

2017-01-15 04:23:18
linear_model.TheilSenRegressor()

class sklearn.linear_model.TheilSenRegressor(fit_intercept=True, copy_X=True, max_subpopulation=10000.0, n_subsamples=None,

2017-01-15 04:23:51
linear_model.OrthogonalMatchingPursuitCV()

class sklearn.linear_model.OrthogonalMatchingPursuitCV(copy=True, fit_intercept=True, normalize=True, max_iter=None

2017-01-15 04:23:37