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[python][sklearn] unify values of best_iteration for sklearn and standard APIs #4845

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Dec 5, 2021
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[python][sklearn] unify values of best_iteration for sklearn and standard APIs #4845

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0e59411
unify values of `best_iteration` for sklearn and standard APIs
StrikerRUS Dec 2, 2021
4f45aff
update Dask test
StrikerRUS Dec 2, 2021
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8 changes: 2 additions & 6 deletions python-package/lightgbm/sklearn.py
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Original file line number Diff line number Diff line change
Expand Up @@ -785,11 +785,7 @@ def _get_meta_data(collection, name, i):
else: # reset after previous call to fit()
self._evals_result = None

if self._Booster.best_iteration != 0:
self._best_iteration = self._Booster.best_iteration
else: # reset after previous call to fit()
self._best_iteration = None

self._best_iteration = self._Booster.best_iteration
self._best_score = self._Booster.best_score

self.fitted_ = True
Expand Down Expand Up @@ -872,7 +868,7 @@ def best_score_(self):

@property
def best_iteration_(self):
""":obj:`int` or :obj:`None`: The best iteration of fitted model if ``early_stopping()`` callback has been specified."""
""":obj:`int`: The best iteration of fitted model if ``early_stopping()`` callback has been specified."""
if not self.__sklearn_is_fitted__():
raise LGBMNotFittedError('No best_iteration found. Need to call fit with early_stopping callback beforehand.')
return self._best_iteration
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2 changes: 1 addition & 1 deletion tests/python_package_test/test_dask.py
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Expand Up @@ -925,7 +925,7 @@ def test_eval_set_no_early_stopping(task, output, eval_sizes, eval_names_prefix,

# check that early stopping was not applied.
assert dask_model.booster_.num_trees() == model_trees
assert dask_model.best_iteration_ is None
assert dask_model.best_iteration_ == 0

# checks that evals_result_ and best_score_ contain expected data and eval_set names.
evals_result = dask_model.evals_result_
Expand Down