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[docs][python] fix shape description of returned result for predict_proba #3933

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Feb 10, 2021
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[docs][python] fix shape description of returned result for predict_proba #3933

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7ad75a1
Update dask.py
StrikerRUS Feb 9, 2021
3d54ba6
Update sklearn.py
StrikerRUS Feb 9, 2021
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8 changes: 4 additions & 4 deletions python-package/lightgbm/dask.py
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Original file line number Diff line number Diff line change
Expand Up @@ -630,7 +630,7 @@ def fit(
fit.__doc__ = (
_base_doc[:_base_doc.find('callbacks :')]
+ '**kwargs\n'
+ ' ' * 12 + 'Other parameters passed through to ``LGBMClassifier.fit()``\n'
+ ' ' * 12 + 'Other parameters passed through to ``LGBMClassifier.fit()``.\n'
)

def predict(self, X: _DaskMatrixLike, **kwargs: Any) -> dask_Array:
Expand Down Expand Up @@ -664,7 +664,7 @@ def predict_proba(self, X: _DaskMatrixLike, **kwargs: Any) -> dask_Array:
description="Return the predicted probability for each class for each sample.",
X_shape="Dask Array or Dask DataFrame of shape = [n_samples, n_features]",
output_name="predicted_probability",
predicted_result_shape="Dask Array of shape = [n_samples, n_classes]",
predicted_result_shape="Dask Array of shape = [n_samples] or shape = [n_samples, n_classes]",
X_leaves_shape="Dask Array of shape = [n_samples, n_trees] or shape = [n_samples, n_trees * n_classes]",
X_SHAP_values_shape="Dask Array of shape = [n_samples, n_features + 1] or shape = [n_samples, (n_features + 1) * n_classes]"
)
Expand Down Expand Up @@ -781,7 +781,7 @@ def fit(
fit.__doc__ = (
_base_doc[:_base_doc.find('callbacks :')]
+ '**kwargs\n'
+ ' ' * 12 + 'Other parameters passed through to ``LGBMRegressor.fit()``\n'
+ ' ' * 12 + 'Other parameters passed through to ``LGBMRegressor.fit()``.\n'
)

def predict(self, X: _DaskMatrixLike, **kwargs) -> dask_Array:
Expand Down Expand Up @@ -922,7 +922,7 @@ def fit(
fit.__doc__ = (
_base_doc[:_base_doc.find('callbacks :')]
+ '**kwargs\n'
+ ' ' * 12 + 'Other parameters passed through to ``LGBMRanker.fit()``\n'
+ ' ' * 12 + 'Other parameters passed through to ``LGBMRanker.fit()``.\n'
)

def predict(self, X: _DaskMatrixLike, **kwargs: Any) -> dask_Array:
Expand Down
2 changes: 1 addition & 1 deletion python-package/lightgbm/sklearn.py
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Original file line number Diff line number Diff line change
Expand Up @@ -933,7 +933,7 @@ def predict_proba(self, X, raw_score=False, start_iteration=0, num_iteration=Non
description="Return the predicted probability for each class for each sample.",
X_shape="array-like or sparse matrix of shape = [n_samples, n_features]",
output_name="predicted_probability",
predicted_result_shape="array-like of shape = [n_samples, n_classes]",
predicted_result_shape="array-like of shape = [n_samples] or shape = [n_samples, n_classes]",
X_leaves_shape="array-like of shape = [n_samples, n_trees] or shape = [n_samples, n_trees * n_classes]",
X_SHAP_values_shape="array-like of shape = [n_samples, n_features + 1] or shape = [n_samples, (n_features + 1) * n_classes] or list with n_classes length of such objects"
)
Expand Down