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Make classifiers and regressors clonable

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This commit is contained in:
Alinson S. Xavier
2021-04-01 07:41:59 -05:00
parent ac29b5213f
commit 820a6256c2
7 changed files with 62 additions and 14 deletions
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4
tests/classifiers/test_adaptive.py
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@@ -15,7 +15,7 @@ def test_adaptive() -> None:
clf = AdaptiveClassifier(
candidates={
"linear": CandidateClassifierSpecs(
classifier=lambda: ScikitLearnClassifier(
classifier=ScikitLearnClassifier(
SVC(
probability=True,
random_state=42,
@@ -23,7 +23,7 @@ def test_adaptive() -> None:
)
),
"poly": CandidateClassifierSpecs(
classifier=lambda: ScikitLearnClassifier(
classifier=ScikitLearnClassifier(
SVC(
probability=True,
kernel="poly",

4
tests/classifiers/test_cv.py
View File

@@ -20,7 +20,7 @@ def test_cv() -> None:
# Support vector machines with linear kernels do not perform well on this
# data set, so predictor should return the given constant.
clf = CrossValidatedClassifier(
classifier=lambda: ScikitLearnClassifier(
classifier=ScikitLearnClassifier(
SVC(
probability=True,
random_state=42,
@@ -41,7 +41,7 @@ def test_cv() -> None:
# Support vector machines with quadratic kernels perform almost perfectly
# on this data set, so predictor should return their prediction.
clf = CrossValidatedClassifier(
classifier=lambda: ScikitLearnClassifier(
classifier=ScikitLearnClassifier(
SVC(
probability=True,
kernel="poly",