code: def fit(self, X, y):
          
          rhl = self._create_random_layer()
          self._genelm_regressor = GenELMRegressor(hidden_layer=rhl,
                                                   regressor=self.regressor)
          self._genelm_regressor.fit(X, y)
          return self
docs: Fit the model using X, y as training data.
  
          Parameters
          ----------
          X : {array-like, sparse matrix} of shape [n_samples, n_features]
              Training vectors, where n_samples is the number of samples
              and n_features is the number of features.
  
          y : array-like of shape [n_samples, n_outputs]
              Target values (class labels in classification, real numbers in
              regression)
  
          Returns
          -------
          self : object
  
              Returns an instance of self.