加入risk_rate freqai属性

freqtrade/templates/freqaiprimer.py

@@ -130,21 +130,51 @@ class FreqaiPrimer(IStrategy):
     }
 
     freqai_info = {
-        "identifier": "freqai_primer_mixed_v6",  # 更新标识符以强制重新训练
+        "identifier": "freqai_primer_mixed_v7",  # 更新标识符以强制重新训练
-        "model": "LightGBMClassifierMultiTarget",  # 多目标分类模型
         "feature_parameters": {
-            "include_timeframes": ["3m", "15m", "1h"],  # 3个时间框架
+            "include_timeframes": ["3m", "15m", "1h"],
             "label_period_candles": 12,
-            "include_shifted_candles": 3,  # 3个shift
+            "include_shifted_candles": 3,
             "include_corr_pairlist": [],
-            "indicator_periods_candles": [10, 20, 50],  # 恢复3个周期以匹配864特征
+            "indicator_periods_candles": [10, 20, 50],
         },
         "data_split_parameters": {
             "test_size": 0.2,
             "shuffle": False,
         },
         "model_training_parameters": {
-            "LightGBMClassifierMultiTarget": {
+            "price_value_divergence": {
+                "model": "LightGBMRegressor",
+                "model_params": {
+                    "n_estimators": 200,
+                    "learning_rate": 0.08,
+                    "num_leaves": 25,
+                    "max_depth": 7,
+                    "min_child_samples": 8,
+                    "subsample": 0.85,
+                    "colsample_bytree": 0.85,
+                    "reg_alpha": 0.08,
+                    "reg_lambda": 0.08,
+                    "verbose": -1,
+                }
+            },
+            "optimal_first_length": {
+                "model": "LightGBMClassifier",
+                "model_params": {
+                    "n_estimators": 200,
+                    "learning_rate": 0.08,
+                    "num_leaves": 25,
+                    "max_depth": 7,
+                    "min_child_samples": 8,
+                    "subsample": 0.85,
+                    "colsample_bytree": 0.85,
+                    "reg_alpha": 0.08,
+                    "reg_lambda": 0.08,
+                    "class_weight": "balanced",
+                    "verbose": -1,
+                }
+            },
+            "risk_rating": {
                 "model": "LightGBMClassifier",
                 "model_params": {
                     "n_estimators": 200,
@@ -163,7 +193,6 @@ class FreqaiPrimer(IStrategy):
         },
         "fit_live_predictions_candles": 100,
         "live_retrain_candles": 100,
-        "multitarget_parallel_training": True,
     }
 
     @staticmethod