Merge pull request #362 from thomas0125/fix_gridsearch

Fix GridSearchCV to support sklearn>=1.3.0

libmultilabel/linear/utils.py

@@ -109,32 +109,31 @@ class GridSearchCV(sklearn.model_selection.GridSearchCV):
  The usage is similar to sklearn's, except that the parameter ``scoring`` is unavailable. Instead, specify ``scoring_metric`` in ``MultiLabelEstimator`` in the Pipeline.
 
  Args:
- pipeline (sklearn.pipeline.Pipeline): A sklearn Pipeline for grid search.
+ estimator (estimator object): An estimator for grid search.
  param_grid (dict): Search space for a grid search containing a dictionary of
  parameters and their corresponding list of candidate values.
  n_jobs (int, optional): Number of CPU cores run in parallel. Defaults to None.
  """
 
- _required_parameters = ["pipeline", "param_grid"]
+ _required_parameters = ["estimator", "param_grid"]
 
- def __init__(self, pipeline: sklearn.pipeline.Pipeline, param_grid: dict, n_jobs=None, **kwargs):
- assert isinstance(pipeline, sklearn.pipeline.Pipeline)
+ def __init__(self, estimator, param_grid: dict, n_jobs=None, **kwargs):
  if n_jobs is not None and n_jobs > 1:
- param_grid = self._set_singlecore_options(pipeline, param_grid)
+ param_grid = self._set_singlecore_options(estimator, param_grid)
  if "scoring" in kwargs.keys():
  raise ValueError(
  "Please specify the validation metric with `MultiLabelEstimator.scoring_metric` in the Pipeline instead of using the parameter `scoring`."
  )
 
- super().__init__(estimator=pipeline, n_jobs=n_jobs, param_grid=param_grid, **kwargs)
+ super().__init__(estimator=estimator, n_jobs=n_jobs, param_grid=param_grid, **kwargs)
 
- def _set_singlecore_options(self, pipeline: sklearn.pipeline.Pipeline, param_grid: dict):
+ def _set_singlecore_options(self, estimator, param_grid: dict):
  """Set liblinear options to `-m 1`. The grid search option `n_jobs`
  runs multiple processes in parallel. Using multithreaded liblinear
  in conjunction with grid search oversubscribes the CPU and deteriorates
  the performance significantly.
  """
- params = pipeline.get_params()
+ params = estimator.get_params()
  for name, transform in params.items():
  if isinstance(transform, MultiLabelEstimator):
  regex = r"-m \d+"

requirements.txt

@@ -2,6 +2,6 @@ liblinear-multicore
 numba
 pandas>1.3.0
 PyYAML
-scikit-learn==1.2.2
+scikit-learn
 scipy
 tqdm

setup.cfg

@@ -1,6 +1,6 @@
 [metadata]
 name = libmultilabel
-version = 0.6.1
+version = 0.6.2
 author = LibMultiLabel Team
 license = MIT License
 license_file = LICENSE
@@ -29,7 +29,7 @@ install_requires =
  numba
  pandas>1.3.0
  PyYAML
- scikit-learn==1.2.2
+ scikit-learn
  scipy
  tqdm