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Merged
merged 9 commits into from
Jun 13, 2024
Merged

array API support for mean_gamma_deviance #29239

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3e70d79
add array API support for mean_gamma_deviance
EmilyXinyi Jun 11, 2024
12bd6ab
reformatted file
EmilyXinyi Jun 11, 2024
a7c9c1b
updated PR number
EmilyXinyi Jun 11, 2024
4fcec35
add array API support for mean_gamma_deviance
EmilyXinyi Jun 11, 2024
820230e
reformatted file
EmilyXinyi Jun 11, 2024
2b57896
updated PR number
EmilyXinyi Jun 11, 2024
98e77ea
addressing review comments - remove extra test and modify existing
EmilyXinyi Jun 12, 2024
ec4281b
resolving conflicts
EmilyXinyi Jun 12, 2024
57b0434
Merge branch 'main' into array_API_mean_gamma_deviance
betatim Jun 13, 2024
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1 change: 1 addition & 0 deletions doc/modules/array_api.rst
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Expand Up @@ -116,6 +116,7 @@ Metrics
- :func:`sklearn.metrics.d2_tweedie_score`
- :func:`sklearn.metrics.max_error`
- :func:`sklearn.metrics.mean_absolute_error`
- :func:`sklearn.metrics.mean_gamma_deviance`
- :func:`sklearn.metrics.mean_squared_error`
- :func:`sklearn.metrics.mean_tweedie_deviance`
- :func:`sklearn.metrics.pairwise.cosine_similarity`
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1 change: 1 addition & 0 deletions doc/whats_new/v1.6.rst
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Expand Up @@ -35,6 +35,7 @@ See :ref:`array_api` for more details.
- :func:`sklearn.metrics.d2_tweedie_score` :pr:`29207` by :user:`Emily Chen <EmilyXinyi>`;
- :func:`sklearn.metrics.max_error` :pr:`29212` by :user:`Edoardo Abati <EdAbati>`;
- :func:`sklearn.metrics.mean_absolute_error` :pr:`27736` by :user:`Edoardo Abati <EdAbati>`;
- :func:`sklearn.metrics.mean_gamma_deviance` :pr:`29239` by :usser:`Emily Chen <EmilyXinyi>`;
- :func:`sklearn.metrics.mean_squared_error` :pr:`29142` by :user:`Yaroslav Korobko <Tialo>`;
- :func:`sklearn.metrics.mean_tweedie_deviance` :pr:`28106` by :user:`Thomas Li <lithomas1>`;
- :func:`sklearn.metrics.pairwise.cosine_similarity` :pr:`29014` by :user:`Edoardo Abati <EdAbati>`.
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2 changes: 1 addition & 1 deletion sklearn/metrics/_regression.py
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Expand Up @@ -1412,7 +1412,7 @@ def mean_tweedie_deviance(y_true, y_pred, *, sample_weight=None, power=0):
raise ValueError(message + "non-negative y and strictly positive y_pred.")
elif power >= 2:
# Gamma and Extreme stable distribution, y and y_pred > 0
if (y_true <= 0).any() or (y_pred <= 0).any():
if xp.any(y_true <= 0) or xp.any(y_pred <= 0):
raise ValueError(message + "strictly positive y and y_pred.")
else: # pragma: nocover
# Unreachable statement
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3 changes: 2 additions & 1 deletion sklearn/metrics/tests/test_common.py
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Expand Up @@ -1827,7 +1827,7 @@ def check_array_api_multiclass_classification_metric(


def check_array_api_regression_metric(metric, array_namespace, device, dtype_name):
y_true_np = np.array([2.0, 0.0, 1.0, 4.0], dtype=dtype_name)
y_true_np = np.array([2.0, 0.1, 1.0, 4.0], dtype=dtype_name)
y_pred_np = np.array([0.5, 0.5, 2, 2], dtype=dtype_name)

metric_kwargs = {}
Expand Down Expand Up @@ -1955,6 +1955,7 @@ def check_array_api_metric_pairwise(metric, array_namespace, device, dtype_name)
check_array_api_regression_metric,
],
paired_cosine_distances: [check_array_api_metric_pairwise],
mean_gamma_deviance: [check_array_api_regression_metric],
max_error: [check_array_api_regression_metric],
}

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