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removing extra tests, as they all raise the same error of min number of classes #15069

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removing extra tests, as they all raise the same error of min number of classes #15069

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removing extra tests, as they all raise the same error of min number …
VariableVasasMT Sep 23, 2019
cc83c35
moving tests in correct order, as they all raise the same error of mi…
VariableVasasMT Sep 23, 2019
1bc46fe
moving tests in correct order, as they all raise the same error of mi…
VariableVasasMT Sep 23, 2019
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7 changes: 4 additions & 3 deletions sklearn/model_selection/tests/test_split.py
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Original file line number Diff line number Diff line change
Expand Up @@ -633,16 +633,17 @@ def test_stratified_shuffle_split_init():
assert_raises(ValueError, next,
StratifiedShuffleSplit(3, 0.2).split(X, y))

X = np.arange(9)
y = np.asarray([0, 0, 0, 1, 1, 1, 2, 2, 2])

# Check that error is raised if the test set size is smaller than n_classes
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@jnothman the test written below wasn't testing what comment said.

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of course I might be wrong in my assumption, I am not sure anymore!

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To avoid confusion in the future, we can use

msg = "The test_size = 2 should be greater or equal to the number of classes = 3"
with pytest.raises(ValueError, match=msg):
    next(StratifiedShuffleSplit(3, 2).split(X, y))

so we can check for the error message explicitly.

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will add these to the messages!

assert_raises(ValueError, next, StratifiedShuffleSplit(3, 2).split(X, y))

# Check that error is raised if the train set size is smaller than
# n_classes
assert_raises(ValueError, next,
StratifiedShuffleSplit(3, 3, 2).split(X, y))

X = np.arange(9)
y = np.asarray([0, 0, 0, 1, 1, 1, 2, 2, 2])

# Train size or test size too small
assert_raises(ValueError, next,
StratifiedShuffleSplit(train_size=2).split(X, y))
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