8000 change bagging to fix travis · scikit-learn/scikit-learn@30ea500 · GitHub
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ngoixngoix
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change bagging to fix travis
1 parent 27b09f8 commit 30ea500

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4 files changed

+11
-10
lines changed

4 files changed

+11
-10
lines changed

‎sklearn/ensemble/bagging.py

Lines changed: 6 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -265,7 +265,12 @@ def fit(self, X, y, sample_weight=None):
265265
else: # float
266266
max_samples = int(self.max_samples * X.shape[0])
267267

268-
if not (0 < max_samples <= X.shape[0]):
268+
if not (max_samples <= X.shape[0]):
269+
warn("max_samples must be less than n_samples."
270+
" The algorithm will use max_samples=n_samples")
271+
max_samples = n_samples
272+
273+
if not (0 < max_samples):
269274
raise ValueError("max_samples must be in (0, n_samples]")
270275

271276
if isinstance(self.max_features, (numbers.Integral, np.integer)):

‎sklearn/ensemble/iforest.py

Lines changed: 0 additions & 5 deletions
Original file line numberDiff line numberDiff line change
@@ -149,11 +149,6 @@ def fit(self, X, y=None, sample_weight=None):
149149

150150
# ensure that max_sample is in [1, n_samples]:
151151
n_samples = X.shape[0]
152-
if not (self.max_samples <= n_samples):
153-
raise ValueError("max_samples (default=256) is greater than the "
154-
"total number of samples")
155-
if not (0 < self.max_samples):
156-
raise ValueError("max_samples has to be positive")
157152

158153
super(IsolationForest, self).fit(X, y, sample_weight=sample_weight)
159154
return self

‎sklearn/ensemble/tests/test_bagging.py

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -387,9 +387,9 @@ def test_error():
387387
BaggingClassifier(base, max_samples=-1).fit, X, y)
388388
assert_raises(ValueError,
389389
BaggingClassifier(base, max_samples=0.0).fit, X, y)
390-
assert_raises(ValueError,
390+
assert_warns(UserWarning,
391391
BaggingClassifier(base, max_samples=2.0).fit, X, y)
392-
assert_raises(ValueError,
392+
assert_warns(UserWarning,
393393
BaggingClassifier(base, max_samples=1000).fit, X, y)
394394
assert_raises(ValueError,
395395
BaggingClassifier(base, max_samples="foobar").fit, X, y)

‎sklearn/ensemble/tests/test_iforest.py

Lines changed: 3 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -12,6 +12,7 @@
1212
from sklearn.utils.testing import assert_array_equal
1313
from sklearn.utils.testing import assert_array_almost_equal
1414
from sklearn.utils.testing import assert_raises
15+
from sklearn.utils.testing import assert_warns
1516

1617
from sklearn.grid_search import GridSearchCV, ParameterGrid
1718
from sklearn.ensemble import IsolationForest
@@ -92,9 +93,9 @@ def test_iforest_error():
9293
IsolationForest(max_samples=-1).fit, X)
9394
assert_raises(ValueError,
9495
IsolationForest(max_samples=0.0).fit, X)
95-
assert_raises(ValueError,
96+
assert_warns(UserWarning,
9697
IsolationForest(max_samples=2.0).fit, X)
97-
assert_raises(ValueError,
98+
assert_warns(UserWarning,
9899
IsolationForest(max_samples=1000).fit, X)
99100
# cannot check for string values
100101

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