class_docstr: Base class for scoring.
  
  Subclass and implement an ``on_*`` method before using.
class_docstr_tok: ["Base","class","for","scoring",".","Subclass","and","implement","an","``","on_","*","``","method","before","using","."]
code: def initialize(self):
      self.best_score_ = np.inf if self.lower_is_better else -np.inf
      self.scoring_ = convert_sklearn_metric_function(self.scoring)
      self.name_ = self._get_name()
      return self
  
imports: from contextlib import contextmanager
  from contextlib import suppress
  from functools import partial
  import warnings
  import numpy
  import sklearn
  from sklearn.metrics import make_scorer, check_scoring
  from skorch.callbacks import Callback
  from skorch.dataset import unpack_data
  from sklearn.metrics._scorer import _BaseScorer
  from skorch.utils import data_from_dataset
  from skorch.utils import is_skorch_dataset
  from skorch.utils import to_numpy
  from skorch.utils import check_indexing
  from skorch.utils import to_device
label_desc: Use image node_id 3 for calling the ScoringBase obj's underlying member method code with example usage: obj.initialize() and returns: self