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Fix label binarize for binary class #5900

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merged 7 commits into from
May 22, 2024
Merged

Fix label binarize for binary class #5900

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743f02d
fix binarization for binary classes
jinsolp May 20, 2024
7c5bf94
add tests for label_binzarize
jinsolp May 20, 2024
713f6f6
fix copyright date
jinsolp May 20, 2024
fe623f9
update based on review
jinsolp May 21, 2024
55b4e83
fix typo in copyright date
jinsolp May 21, 2024
7bda331
styling
jinsolp May 21, 2024
e1c346b
fix styling
jinsolp May 21, 2024
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9 changes: 7 additions & 2 deletions python/cuml/preprocessing/label.py
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Original file line number Diff line number Diff line change
@@ -1,4 +1,4 @@
# Copyright (c) 2020-2023, NVIDIA CORPORATION.
# Copyright (c) 2020-2024, NVIDIA CORPORATION.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
Expand Down Expand Up @@ -64,14 +64,19 @@ def label_binarize(

cp.cuda.Stream.null.synchronize()

is_binary = classes.shape[0] == 2

if sparse_output:
sp = sp.tocsr()
if is_binary:
sp = sp.getcol(1) # getcol does not support -1 indexing
return sp
else:

arr = sp.toarray().astype(y.dtype)
arr[arr == 0] = neg_label

if is_binary:
arr = arr[:, -1].reshape((-1, 1))
return arr


Expand Down
34 changes: 33 additions & 1 deletion python/cuml/tests/test_preprocessing.py
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Original file line number Diff line number Diff line change
@@ -1,4 +1,4 @@
# Copyright (c) 2020-2023, NVIDIA CORPORATION.
# Copyright (c) 2020-2024, NVIDIA CORPORATION.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
Expand Down Expand Up @@ -43,6 +43,7 @@
quantile_transform as cu_quantile_transform,
robust_scale as cu_robust_scale,
scale as cu_scale,
label_binarize as cu_label_binarize,
)
from sklearn.preprocessing import (
Binarizer as skBinarizer,
Expand All @@ -68,6 +69,7 @@
quantile_transform as sk_quantile_transform,
robust_scale as sk_robust_scale,
scale as sk_scale,
label_binarize as sk_label_binarize,
)
from sklearn.impute import (
MissingIndicator as skMissingIndicator,
Expand Down Expand Up @@ -1135,6 +1137,36 @@ def test_kernel_centerer():
assert_allclose(sk_t_X, t_X)


def test_label_binarize():
cu_bin = cu_label_binarize(
cp.array([1, 0, 1, 1]), classes=cp.array([0, 1])
)
sk_bin = sk_label_binarize([1, 0, 1, 1], classes=[0, 1])
assert_allclose(cu_bin, sk_bin)

cu_bin_sparse = cu_label_binarize(
cp.array([1, 0, 1, 1]), classes=cp.array([0, 1]), sparse_output=True
)
sk_bin_sparse = sk_label_binarize(
[1, 0, 1, 1], classes=[0, 1], sparse_output=True
)
assert_allclose(cu_bin_sparse, sk_bin_sparse)

cu_multi = cu_label_binarize(
cp.array([1, 6, 3]), classes=cp.array([1, 3, 4, 6])
)
sk_multi = sk_label_binarize([1, 6, 3], classes=[1, 3, 4, 6])
assert_allclose(cu_multi, sk_multi)

cu_multi_sparse = cu_label_binarize(
cp.array([1, 6, 3]), classes=cp.array([1, 3, 4, 6]), sparse_output=True
)
sk_multi_sparse = sk_label_binarize(
[1, 6, 3], classes=[1, 3, 4, 6], sparse_output=True
)
assert_allclose(cu_multi_sparse, sk_multi_sparse)


def test__repr__():
assert cuBinarizer().__repr__() == "Binarizer()"
assert cuFunctionTransformer().__repr__() == "FunctionTransformer()"
Expand Down
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