class_docstr: Estimator for which we can turn on/off the prediction methods.
  
  Parameters
  ----------
  response_methods: list of             {"predict", "predict_proba", "decision_function"}, default=None
      List containing the response implemented by the estimator. When, the
      response is in the list, it will return the name of the response method
      when called. Otherwise, an `AttributeError` is raised. It allows to
      use `getattr` as any conventional estimator. By default, no response
      methods are mocked.
code: def fit(self, X, y):
      self.classes_ = np.unique(y)
      return self
  
imports: import numpy
  from ..base import BaseEstimator, ClassifierMixin
  from ..utils._metadata_requests import RequestMethod
  from .metaestimators import available_if
  from .validation import _check_sample_weight, _num_samples, check_array, check_is_fitted
label_desc: Use image node_id 2 for calling the _MockEstimatorOnOffPrediction obj's underlying member method code with example usage: obj.fit(X, y) and returns: self