code: def _create_model(self, X, Y):
          
          from sklearn.ensemble import RandomForestRegressor
          self.X = X
          self.Y = Y
          self.model = RandomForestRegressor(bootstrap = self.bootstrap,
                                             criterion = self.criterion,
                                             max_depth = self.max_depth,
                                             max_features = self.max_features,
                                             max_leaf_nodes = self.max_leaf_nodes,
                                             min_samples_leaf = self.min_samples_leaf,
                                             min_samples_split = self.min_samples_split,
                                             min_weight_fraction_leaf = self.min_weight_fraction_leaf,
                                             n_estimators = self.n_estimators,
                                             n_jobs = self.n_jobs,
                                             oob_score = self.oob_score,
                                             random_state = self.random_state,
                                             verbose = self.verbose,
                                             warm_start = self.warm_start)
  
          #self.model = RandomForestRegressor()
          self.model.fit(X,Y.flatten())
docs: Creates the model given some input data X and Y.