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FIX bug in SplineTransformer.n_features_out_ #19577

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Merged
merged 3 commits into from
Feb 27, 2021
Merged

FIX bug in SplineTransformer.n_features_out_ #19577

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fcfd570
Start off with a failing test.
mlondschien Feb 26, 2021
68dfd92
Fix attribute.
mlondschien Feb 26, 2021
e613c5c
Parametrize n_knots.
mlondschien Feb 27, 2021
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4 changes: 2 additions & 2 deletions sklearn/preprocessing/_polynomial.py
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Original file line number Diff line number Diff line change
Expand Up @@ -307,7 +307,7 @@ def fit(self, X, y=None):
]
self.bsplines_ = bsplines

self.n_features_out_ = n_out - n_features * self.include_bias
self.n_features_out_ = n_out - n_features * (1 - self.include_bias)
return self

def transform(self, X):
Expand Down Expand Up @@ -336,7 +336,7 @@ def transform(self, X):

# Note that scipy BSpline returns float64 arrays and converts input
# x=X[:, i] to c-contiguous float64.
n_out = self.n_features_out_ + n_features * self.include_bias
n_out = self.n_features_out_ + n_features * (1 - self.include_bias)
if X.dtype in FLOAT_DTYPES:
dtype = X.dtype
else:
Expand Down
16 changes: 16 additions & 0 deletions sklearn/preprocessing/tests/test_polynomial.py
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Expand Up @@ -243,3 +243,19 @@ def test_spline_transformer_kbindiscretizer():
# Though they should be exactly equal, we test approximately with high
# accuracy.
assert_allclose(splines, kbins, rtol=1e-13)


@pytest.mark.parametrize("n_knots", [5, 10])
@pytest.mark.parametrize("include_bias", [True, False])
@pytest.mark.parametrize("degree", [3, 5])
def test_spline_transformer_n_features_out(n_knots, include_bias, degree):
"""Test that transform results in n_features_out_ features."""
splt = SplineTransformer(
n_knots=n_knots,
degree=degree,
include_bias=include_bias
)
X = np.linspace(0, 1, 10)[:, None]
splt.fit(X)

assert splt.transform(X).shape[1] == splt.n_features_out_