sklearn.linear_model.lars_path 파라미터

lars_path

sklearn.linear_model.lars_path(X, y, Xy=None, *, Gram=None, max_iter=500, alpha_min=0, method='lar', copy_X=True, eps=2.220446049250313e-16, copy_Gram=True, verbose=0, return_path=True, return_n_iter=False, positive=False)

 

lars_path 파라미터

XNone or array-like of shape (n_samples, n_features)

yNone or array-like of shape (n_samples,)

Xyarray-like of shape (n_samples,) or (n_samples, n_targets), 기본값=None

GramNone, ‘auto’, array-like of shape (n_features, n_features), 기본값=None

max_iterint, 기본값=500

alpha_minfloat, 기본값=0

method{‘lar’, ‘lasso’}, 기본값=’lar’

copy_Xbool, 기본값=True

epsfloat, 기본값=np.finfo(float).eps

copy_Grambool, 기본값=True

verboseint, 기본값=0

return_pathbool, 기본값=True

return_n_iterbool, 기본값=False

positivebool, 기본값=False