训练一直报错

config_examples/live_XGBoostRegressorMultiTarget.json

@@ -71,64 +71,79 @@
     "use_order_book": false
   },
   "freqai": {
-    "enabled": true,
-    "data_kitchen": {
-      "fillna": "ffill"
-    },
-    "freqaimodel": "XGBoostRegressorMultiTarget",
-    "purge_old_models": 2,
-    "identifier": "live-freqai",
-    "train_period_days": 18,
-    "backtest_period_days": 2,
-    "live_retrain_hours": 2,
-    "outlier_detection": {
-      "method": "IsolationForest",
-      "contamination": 0.05  // 适度提高异常值检测阈值，过滤更多噪声
-    },
-    "feature_selection": {
-      "method": "recursive_elimination",
-    },
-    "feature_parameters": {
-      "include_timeframes": [
-        "3m",
-        "15m",
-        "1h",
-        "4h"
-      ],
-      "include_corr_pairlist": [
-        "XAUT/USDT",
-        "BTC/USDT"
-      ],
-      "outlier_protection_percentage": 0.05,
-      "label_period_candles": 100,
-      "include_shifted_candles": 2,  // 减少移位蜡烛数，降低特征冗余
-      "DI_threshold": 0.1,
-      "weight_factor": 0.9,
-      "principal_component_analysis": true,  // 开启PCA降维，减少特征维度
-      "use_SVM_to_remove_outliers": false,
-      "buffer_train_data_candles": 30,  // 增加缓冲区数据
-      "indicator_periods_candles": [
-        10,
-        20,
-        50  // 减少指标周期数，避免特征过多
-      ],
-      "plot_feature_importances": 10
-    },
-    "data_split_parameters": {
-      "test_size": 0.2,  // 增大测试集比例，更严格验证模型泛化能力
-      "shuffle": false
-    },
-    "model_training_parameters": {
-      "n_estimators": 200,  // 减少树的数量，降低模型复杂度
-      "learning_rate": 0.05,  // 适度提高学习率，加快收敛且避免过拟合
-      "max_depth": 5,  // 降低树深度，核心缓解过拟合
-      "min_child_weight": 3,  // 提高子节点最小权重，避免拟合噪声
-      "subsample": 0.7,  // 降低样本采样率，增强正则化
-      "colsample_bytree": 0.7,  // 降低特征采样率，避免过拟合
-      "verbosity": 0,
-      "reg_alpha": 0.1,  // 新增L1正则化，限制权重
-      "reg_lambda": 1.0  // 新增L2正则化，核心缓解过拟合
-    }
+      "enabled": true,
+      "data_kitchen": {
+          "fillna": "ffill"
+      },
+      "freqaimodel": "XGBoostRegressorMultiTarget",
+      "purge_old_models": 2,
+      "train_period_days": 18,
+      "backtest_period_days": 2,
+      "live_retrain_hours": 2,
+      "outlier_detection": {
+          "method": "IsolationForest",
+          "contamination": 0.05
+      },
+      "feature_selection": {
+          "method": "recursive_elimination"
+      },
+      "feature_parameters": {
+          "include_timeframes": [
+              "3m",
+              "15m",
+              "1h",
+              "4h"
+          ],
+          "include_corr_pairlist": [
+              "XAUT/USDT",
+              "BTC/USDT"
+          ],
+          "outlier_protection_percentage": 0.05,
+          "label_period_candles": 100,
+          "include_shifted_candles": 2,
+          "DI_threshold": 0.1,
+          "weight_factor": 0.9,
+          "principal_component_analysis": true,
+          "use_SVM_to_remove_outliers": false,
+          "indicator_periods_candles": [
+              10,
+              20,
+              50
+          ],
+          "plot_feature_importances": 10,
+          "buffer_train_data_candles": 30,
+          "shuffle_after_split": false
+      },
+      "data_split_parameters": {
+          "test_size": 0.2,
+          "shuffle": false
+      },
+      "model_training_parameters": {
+          "n_estimators": 200,
+          "learning_rate": 0.05,
+          "num_leaves": 60,
+          "max_depth": 5,
+          "min_data_in_leaf": 15,
+          "feature_fraction": 0.8,
+          "bagging_fraction": 0.8,
+          "bagging_freq": 5,
+          "verbose": -1,
+          "min_child_weight": 3,
+          "subsample": 0.7,
+          "colsample_bytree": 0.7,
+          "verbosity": 0,
+          "reg_alpha": 0.1,
+          "reg_lambda": 1.0
+      },
+      "identifier": "live-freqai",
+      "write_metrics_to_disk": false,
+      "conv_width": 1,
+      "expiration_hours": 0,
+      "save_backtest_models": false,
+      "activate_tensorboard": true,
+      "wait_for_training_iteration_on_reload": true,
+      "continual_learning": false,
+      "keras": false
   },
   "fee": 0.0008,
   "api_server": {