贝叶斯调参优化

main.py

@@ -84,7 +84,7 @@ class LightGBM(object):
             categorical_feature=["uid", "type", "channel", "mode", "out_user_id", "tag1", "tag2", "tag3"],
         )
         test_data = lgb.Dataset(X_test, label=Y_test, reference=train_data)
-        gbm = lgb.train(param, train_data, num_boost_round=100, valid_sets=[test_data], early_stopping_rounds=10, verbose_eval=False)
+        gbm = lgb.train(param, train_data, num_boost_round=100, valid_sets=[test_data])
         preds = gbm.predict(X_test)
         pred_labels = np.rint(preds)
         accuracy = accuracy_score(Y_test, pred_labels)