8000 Fixed pep8 violations and sampleweight format · scikit-learn/scikit-learn@113d048 · GitHub
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Fixed pep8 violations and sampleweight format
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-7
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‎sklearn/svm/classes.py

Lines changed: 0 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -366,10 +366,6 @@ def fit(self, X, y, sample_weight=None):
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if self.C < 0:
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raise ValueError("Penalty term must be positive; got (C=%r)"
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% self.C)
369-
if ((sample_weight is not None) and
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np.atleast_1d(sample_weight).ndim > 1):
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sample_weight = column_or_1d(sample_weight, warn=True)
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X, y = check_X_y(X, y, accept_sparse='csr',
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dtype=np.float64, order="C")
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penalty = 'l2' # SVR only accepts l2 penalty

‎sklearn/svm/tests/test_svm.py

Lines changed: 7 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -196,9 +196,11 @@ def test_linearsvr():
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svr = svm.SVR(kernel='linear', C=1e3).fit(diabetes.data, diabetes.target)
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score2 = svr.score(diabetes.data, diabetes.target)
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199-
assert_allclose( np.linalg.norm(lsvr.coef_) , np.linalg.norm(svr.coef_),1, 0.0001 )
199+
assert_allclose(np.linalg.norm(lsvr.coef_),
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np.linalg.norm(svr.coef_), 1, 0.0001)
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assert_almost_equal(score1, score2, 2)
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203+
202204
def test_linearsvr_fit_sampleweight():
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# check correct result when sample_weight is 1
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# check that SVR(kernel='linear') and LinearSVC() give
@@ -213,7 +215,8 @@ def test_linearsvr_fit_sampleweight():
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lsvr_no_weight = svm.LinearSVR(C=1e3).fit(diabetes.data, diabetes.target)
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score2 = lsvr_no_weight.score(diabetes.data, diabetes.target)
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216-
assert_allclose(np.linalg.norm(lsvr.coef_), np.linalg.norm(lsvr_no_weight.coef_), 1, 0.0001)
218+
assert_allclose(np.linalg.norm(lsvr.coef_),
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np.linalg.norm(lsvr_no_weight.coef_), 1, 0.0001)
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assert_almost_equal(score1, score2, 2)
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# check that fit(X) = fit([X1, X2, X3],sample_weight = [n1, n2, n3]) where
@@ -230,7 +233,8 @@ def test_linearsvr_fit_sampleweight():
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lsvr_flat = svm.LinearSVR(C=1e3).fit(X_flat, y_flat)
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score4 = lsvr_flat.score(X_flat, y_flat)
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233-
assert_almost_equal(score3 ,score4,2)
236+
assert_almost_equal(score3, score4, 2)
237+
234238

235239
def test_svr_errors():
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X = [[0.0], [1.0]]

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