Rename clf to reg

sklearn/linear_model/least_angle.py

@@ -570,13 +570,13 @@ class Lars(LinearModel, RegressorMixin):
     Examples
     --------
     >>> from sklearn import linear_model
-    >>> clf = linear_model.Lars(n_nonzero_coefs=1)
-    >>> clf.fit([[-1, 1], [0, 0], [1, 1]], [-1.1111, 0, -1.1111])
+    >>> reg = linear_model.Lars(n_nonzero_coefs=1)
+    >>> reg.fit([[-1, 1], [0, 0], [1, 1]], [-1.1111, 0, -1.1111])
     ... # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
     Lars(copy_X=True, eps=..., fit_intercept=True, fit_path=True,
        n_nonzero_coefs=1, normalize=True, positive=False, precompute='auto',
        verbose=False)
-    >>> print(clf.coef_) # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
+    >>> print(reg.coef_) # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
     [ 0. -1.11...]
 
     See also
@@ -805,13 +805,13 @@ class LassoLars(Lars):
     Examples
     --------
     >>> from sklearn import linear_model
-    >>> clf = linear_model.LassoLars(alpha=0.01)
-    >>> clf.fit([[-1, 1], [0, 0], [1, 1]], [-1, 0, -1])
+    >>> reg = linear_model.LassoLars(alpha=0.01)
+    >>> reg.fit([[-1, 1], [0, 0], [1, 1]], [-1, 0, -1])
     ... # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
     LassoLars(alpha=0.01, copy_X=True, eps=..., fit_intercept=True,
          fit_path=True, max_iter=500, normalize=True, positive=False,
          precompute='auto', verbose=False)
-    >>> print(clf.coef_) # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
+    >>> print(reg.coef_) # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
     [ 0.         -0.963257...]
 
     See also
@@ -1408,13 +1408,13 @@ class LassoLarsIC(LassoLars):
     Examples
     --------
     >>> from sklearn import linear_model
-    >>> clf = linear_model.LassoLarsIC(criterion='bic')
-    >>> clf.fit([[-1, 1], [0, 0], [1, 1]], [-1.1111, 0, -1.1111])
+    >>> reg = linear_model.LassoLarsIC(criterion='bic')
+    >>> reg.fit([[-1, 1], [0, 0], [1, 1]], [-1.1111, 0, -1.1111])
     ... # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
     LassoLarsIC(copy_X=True, criterion='bic', eps=..., fit_intercept=True,
           max_iter=500, normalize=True, positive=False, precompute='auto',
           verbose=False)
-    >>> print(clf.coef_) # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
+    >>> print(reg.coef_) # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
     [ 0.  -1.11...]
 
     Notes