class_docstr: Sampler without target checking.
class_docstr_tok: ["Sampler","without","target","checking","."]
code: def fit(self, X, y):
      X, y = self._validate_data(X, y)
      return self
  
imports: import numpy
  import pytest
  from sklearn.base import BaseEstimator
  from sklearn.utils.multiclass import check_classification_targets
  from imblearn.base import BaseSampler
  from imblearn.over_sampling.base import BaseOverSampler
  from imblearn.utils import check_target_type
  from imblearn.utils.estimator_checks import check_samplers_fit, check_samplers_nan, check_samplers_one_label, check_samplers_preserve_dtype, check_samplers_sparse, check_samplers_string, check_target_type
label_desc: Use image node_id 1 for calling the NotFittedSampler obj's underlying member method code with example usage: obj.fit(X, y) and returns: self