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.PassiveAggressiveRegressor()

class sklearn.linear_model.PassiveAggressiveRegressor(C=1.0, fit_intercept=True, n_iter=5, shuffle=True, verbose=0

2017-01-15 04:23:39
linear_model.BayesianRidge()

class sklearn.linear_model.BayesianRidge(n_iter=300, tol=0.001, alpha_1=1e-06, alpha_2=1e-06, lambda_1=1e-06, lambda_2=1e-06, compute_score=False

2017-01-15 04:23:15
linear_model.MultiTaskElasticNet()

class sklearn.linear_model.MultiTaskElasticNet(alpha=1.0, l1_ratio=0.5, fit_intercept=True, normalize=False, copy_X=True,

2017-01-15 04:23:32
linear_model.Lars()

class sklearn.linear_model.Lars(fit_intercept=True, verbose=False, normalize=True, precompute='auto', n_nonzero_coefs=500, eps=2.2204460492503131e-16

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

class sklearn.linear_model.RANSACRegressor(base_estimator=None, min_samples=None, residual_threshold=None, is_data_valid=None

2017-01-15 04:23:43
linear_model.RidgeClassifierCV()

class sklearn.linear_model.RidgeClassifierCV(alphas=(0.1, 1.0, 10.0), fit_intercept=True, normalize=False, scoring=None, cv=None

2017-01-15 04:23:47
linear_model.LassoLarsIC()

class sklearn.linear_model.LassoLarsIC(criterion='aic', fit_intercept=True, verbose=False, normalize=True, precompute='auto', max_iter=500

2017-01-15 04:23:26
linear_model.LassoLarsCV()

class sklearn.linear_model.LassoLarsCV(fit_intercept=True, verbose=False, max_iter=500, normalize=True, precompute='auto', cv=None

2017-01-15 04:23:25
linear_model.LassoCV()

class sklearn.linear_model.LassoCV(eps=0.001, n_alphas=100, alphas=None, fit_intercept=True, normalize=False, precompute='auto', max_iter=1000

2017-01-15 04:23:23