class_docstr: A :py:class:`~ray.train.Checkpoint` with sklearn-specific functionality.
class_docstr_tok: ["A",":","py",":","class",":","`","~ray.train.Checkpoint","`","with","sklearn-specific","functionality","."]
docstr: Retrieve the ``Estimator`` stored in this checkpoint.
docstr_tok: ["Retrieve","the","``","Estimator","``","stored","in","this","checkpoint","."]
code: def get_estimator(self) -> BaseEstimator:
      """Retrieve the ``Estimator`` stored in this checkpoint."""
      with self.as_directory() as checkpoint_path:
          estimator_path = os.path.join(
              checkpoint_path, self.MODEL_FILENAME
          )
          with open(estimator_path, "rb") as f:
              return cpickle.load(f)
  
file_path: ray/python/ray/train/sklearn/sklearn_checkpoint.py
imports: import os
  import tempfile
  from typing import TYPE_CHECKING, Optional, Union
  from sklearn.base import BaseEstimator
  import ray.cloudpickle
  from ray.train._internal.framework_checkpoint import FrameworkCheckpoint
  from ray.util.annotations import PublicAPI
label_desc: Use image node_id 2 for calling the SklearnCheckpoint obj's underlying member method code with example usage: obj.get_estimator() and returns: cpickle