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MAINT Parameters validation for metrics.fbeta_score #25840

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33 changes: 28 additions & 5 deletions sklearn/metrics/_classification.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1227,6 +1227,25 @@ def f1_score(
)


@validate_params(
{
"y_true": ["array-like", "sparse matrix"],
"y_pred": ["array-like", "sparse matrix"],
"beta": [Interval(Real, 0.0, None, closed="both")],
"labels": ["array-like", None],
"pos_label": [Real, str, "boolean", None],
"average": [
StrOptions({"micro", "macro", "samples", "weighted", "binary"}),
None,
],
"warn_for": [list, tuple, set],
"sample_weight": ["array-like", None],
"zero_division": [
Options(Real, {0, 1}),
StrOptions({"warn"}),
],
}
)
def fbeta_score(
y_true,
y_pred,
Expand Down Expand Up @@ -2743,9 +2762,11 @@ def log_loss(
else:
# TODO: Remove user defined eps in 1.5
warnings.warn(
"Setting the eps parameter is deprecated and will "
"be removed in 1.5. Instead eps will always have"
"a default value of `np.finfo(y_pred.dtype).eps`.",
(
"Setting the eps parameter is deprecated and will "
"be removed in 1.5. Instead eps will always have"
"a default value of `np.finfo(y_pred.dtype).eps`."
),
FutureWarning,
)

Expand Down Expand Up @@ -2812,8 +2833,10 @@ def log_loss(
y_pred_sum = y_pred.sum(axis=1)
if not np.isclose(y_pred_sum, 1, rtol=1e-15, atol=5 * eps).all():
warnings.warn(
"The y_pred values do not sum to one. Starting from 1.5 this"
"will result in an error.",
(
"The y_pred values do not sum to one. Starting from 1.5 this"
"will result in an error."
),
UserWarning,
)
y_pred = y_pred / y_pred_sum[:, np.newaxis]
Expand Down
1 change: 1 addition & 0 deletions sklearn/tests/test_public_functions.py
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Expand Up @@ -137,6 +137,7 @@ def _check_function_param_validation(
"sklearn.metrics.dcg_score",
"sklearn.metrics.det_curve",
"sklearn.metrics.f1_score",
"sklearn.metrics.fbeta_score",
"sklearn.metrics.get_scorer",
"sklearn.metrics.hamming_loss",
"sklearn.metrics.jaccard_score",
Expand Down