code: def predict(self, X):
          
          jll = self._joint_log_likelihood(X)
          return self.classes_[np.argmax(jll, axis=1)]
docs: Perform classification on an array of test vectors X.
  
          Parameters
          ----------
          X : array-like, shape = [n_samples, n_features]
  
          Returns
          -------
          C : array, shape = [n_samples]
              Predicted target values for X