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Fix doctest
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holgern committed Jun 4, 2024
1 parent 47a903c commit 23dce51
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Showing 7 changed files with 8 additions and 30 deletions.
2 changes: 1 addition & 1 deletion doc/conf.py
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Expand Up @@ -289,7 +289,7 @@ def __init__(self, src_dir):
self.regex = re.compile(r"^([\w ]+)\n-", re.MULTILINE)

def __repr__(self):
return f'<{self.__class__.__name__}>'
return '<%s: %s>' % (self.__class__.__name__, self.src_dir)

def __call__(self, directory):
src_path = os.path.normpath(os.path.join(self.src_dir, directory))
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7 changes: 0 additions & 7 deletions doc/modules/benchmarks.rst

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7 changes: 0 additions & 7 deletions doc/modules/learning.rst

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6 changes: 0 additions & 6 deletions doc/modules/sampler.rst

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6 changes: 0 additions & 6 deletions doc/modules/transformers.rst

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6 changes: 3 additions & 3 deletions doc/whats_new/v0.10.rst
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Expand Up @@ -5,16 +5,17 @@
.. _changes_0_10_1:

Version 0.10.1
=============
==============
**March 2024**

- |Fix| Typo in skopt/space/space.py

.. _changes_0_10:

Version 0.10.0
=============
==============
**March 2024**

- |Feature| Add support for multimetric scoring to :obj:`skopt.searchcv.BayesSearchCV`.
- |Feature| Evaluate random point instead of using point twice in :obj:`skopt.optimizer.Optimizer`.
- |Feature| :obj:`skopt.callback.CheckpointSaver` can now recycle previous function evaluations
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would change under the new scheme.
- Minor documentation improvements.
- Various small bugs and fixes.

4 changes: 4 additions & 0 deletions skopt/searchcv.py
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Expand Up @@ -87,13 +87,17 @@ class BayesSearchCV(BaseSearchCV):
the test set. If ``None``, the ``score`` method of the estimator is
used.
If `scoring` represents a single score, one can use:
- a single string (see :ref:`scoring_parameter`);
- a callable (see :ref:`scoring`) that returns a single value.
If `scoring` represents multiple scores, one can use:
- a list or tuple of unique strings;
- a callable returning a dictionary where the keys are the metric
names and the values are the metric scores;
- a dictionary with metric names as keys and callables a values.
Callables must have the signature ``scorer(estimator, X, y=None)``
fit_params : dict, optional
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