[python][examples] updated examples with multiple custom metrics (#3367)

examples/python-guide/advanced_example.py

@@ -186,8 +186,7 @@ gbm = lgb.train(params,
                 num_boost_round=10,
                 init_model=gbm,
                 fobj=loglikelihood,
-                feval=lambda preds, train_data: [binary_error(preds, train_data),
-                                                 accuracy(preds, train_data)],
+                feval=[binary_error, accuracy],
                 valid_sets=lgb_eval)
 
 print('Finished 50 - 60 rounds with self-defined objective function '

examples/python-guide/sklearn_example.py

@@ -62,7 +62,7 @@ print('Starting training with multiple custom eval functions...')
 # train
 gbm.fit(X_train, y_train,
         eval_set=[(X_test, y_test)],
-        eval_metric=lambda y_true, y_pred: [rmsle(y_true, y_pred), rae(y_true, y_pred)],
+        eval_metric=[rmsle, rae],
         early_stopping_rounds=5)
 
 print('Starting predicting...')