更新初始化代码

main.py

@@ -56,6 +56,8 @@ with open("whole_data/x_data_3day_up_level.json") as f1:
     for key in float_cols:
         X_test[key] = pd.to_numeric(X_test[key], errors='coerce')
 
+print("读取X数据成功！")
+
 
 with open("whole_data/y_data_3day_up_level.json") as f2:
     y_list = json.loads(f2.read())
@@ -66,10 +68,14 @@ with open("whole_data/y_data_3day_up_level.json") as f2:
     y_train = np.array(y_list[:index_t])
     y_test = np.array(y_list[index_t:])
 
+print("读取Y数据成功！")
+
+
 # 创建LightGBM数据集
 train_data = lgb.Dataset(X_train, label=y_train, categorical_feature=['uid', 'type', 'channel', 'mode', 'out_user_id'])
 test_data = lgb.Dataset(X_test, label=y_test, reference=train_data)
 
+print("数据集创建成功")
 # 设置模型的参数
 params = {
     'objective': 'binary',  # 指定二分类任务
@@ -83,8 +89,9 @@ params = {
 
 # 训练模型
 num_round = 100
+print("开始训练......")
 bst = lgb.train(params, train_data, num_round, valid_sets=[test_data])
-
+print("训练完成! , 开始预测......")
 # 预测
 y_pred = bst.predict(X_test, num_iteration=bst.best_iteration)
 # 转换为二进制输出