@@ -570,13 +570,13 @@ class Lars(LinearModel, RegressorMixin):
570570 Examples
571571 --------
572572 >>> from sklearn import linear_model
573- >>> clf = linear_model.Lars(n_nonzero_coefs=1)
574- >>> clf .fit([[-1, 1], [0, 0], [1, 1]], [-1.1111, 0, -1.1111])
573+ >>> reg = linear_model.Lars(n_nonzero_coefs=1)
574+ >>> reg .fit([[-1, 1], [0, 0], [1, 1]], [-1.1111, 0, -1.1111])
575575 ... # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
576576 Lars(copy_X=True, eps=..., fit_intercept=True, fit_path=True,
577577 n_nonzero_coefs=1, normalize=True, positive=False, precompute='auto',
578578 verbose=False)
579- >>> print(clf .coef_) # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
579+ >>> print(reg .coef_) # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
580580 [ 0. -1.11...]
581581
582582 See also
@@ -805,13 +805,13 @@ class LassoLars(Lars):
805805 Examples
806806 --------
807807 >>> from sklearn import linear_model
808- >>> clf = linear_model.LassoLars(alpha=0.01)
809- >>> clf .fit([[-1, 1], [0, 0], [1, 1]], [-1, 0, -1])
808+ >>> reg = linear_model.LassoLars(alpha=0.01)
809+ >>> reg .fit([[-1, 1], [0, 0], [1, 1]], [-1, 0, -1])
810810 ... # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
811811 LassoLars(alpha=0.01, copy_X=True, eps=..., fit_intercept=True,
812812 fit_path=True, max_iter=500, normalize=True, positive=False,
813813 precompute='auto', verbose=False)
814- >>> print(clf .coef_) # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
814+ >>> print(reg .coef_) # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
815815 [ 0. -0.963257...]
816816
817817 See also
@@ -1408,13 +1408,13 @@ class LassoLarsIC(LassoLars):
14081408 Examples
14091409 --------
14101410 >>> from sklearn import linear_model
1411- >>> clf = linear_model.LassoLarsIC(criterion='bic')
1412- >>> clf .fit([[-1, 1], [0, 0], [1, 1]], [-1.1111, 0, -1.1111])
1411+ >>> reg = linear_model.LassoLarsIC(criterion='bic')
1412+ >>> reg .fit([[-1, 1], [0, 0], [1, 1]], [-1.1111, 0, -1.1111])
14131413 ... # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
14141414 LassoLarsIC(copy_X=True, criterion='bic', eps=..., fit_intercept=True,
14151415 max_iter=500, normalize=True, positive=False, precompute='auto',
14161416 verbose=False)
1417- >>> print(clf .coef_) # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
1417+ >>> print(reg .coef_) # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
14181418 [ 0. -1.11...]
14191419
14201420 Notes
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