Update model_predictor.py

model_predictor.py

@@ -23,14 +23,14 @@ class XGBoostModel:
         # ***FIXED: Updated feature columns to match the training script***
         self.feature_columns = [
             'close',
-            'return-t-1',
-            'return-t-5',
+            'return_t-1',
+            'return_t-5',
             'MA5_close',
             'volatility_5d',
             'volume_ratio_5d',
             'MACD_diff',
-            'dji_return-t-1',
-            'sox_return-t-1',
+            'dji_return_t-1',
+            'sox_return_t-1',
             'NEWS',
             'MACDvol',
             'RSI_14',
@@ -128,16 +128,16 @@ class XGBoostModel:
         df['volume'] = df['Volume']
         
         # 1. return-t-1 — 前一日報酬率 (***FIXED: Corrected to use hyphen***)
-        df['return-t-1'] = df['close'].pct_change()
+        df['return_t-1'] = df['close'].pct_change()
         
         # 2. return-t-5 — 過去 5 日累積報酬率 (***FIXED: Corrected to use hyphen***)
-        df['return-t-5'] = (df['close'] / df['close'].shift(5) - 1)
+        df['return_t-5'] = (df['close'] / df['close'].shift(5) - 1)
         
         # 3. MA5_close — 5 日移動平均價
         df['MA5_close'] = df['close'].rolling(window=5).mean()
         
         # 4. volatility_5d — 5 日報酬標準差
-        df['volatility_5d'] = df['return-t-1'].rolling(window=5).std()
+        df['volatility_5d'] = df['return_t-1'].rolling(window=5).std()
         
         # 5. volume_ratio_5d — 今日成交量 ÷ 5 日均量
         df['volume_5d_avg'] = df['volume'].rolling(window=5).mean()
@@ -151,8 +151,8 @@ class XGBoostModel:
         df['MACD_diff'] = macd_line - signal_line
         
         # 7-8. 美股指數報酬率（需要外部資料，暫設為0）
-        df['dji_return-t-1'] = 0.0
-        df['sox_return-t-1'] = 0.0
+        df['dji_return_t-1'] = 0.0
+        df['sox_return_t-1'] = 0.0
         
         # 9. NEWS — 新聞情緒分數（需要外部資料，暫設為0）
         df['NEWS'] = 0.0
@@ -184,7 +184,7 @@ class XGBoostModel:
         df['ADX'] = df['DX'].ewm(com=13, adjust=False).mean()
         
         # 13. volume_weighted_return — 成交量加權報酬率
-        df['volume_weighted_return'] = np.abs(df['return-t-1']) * df['volume']
+        df['volume_weighted_return'] = np.abs(df['return_t-1']) * df['volume']
         
         # 清理輔助欄位
         cleanup_columns = ['volume_5d_avg', 'up_move', 'down_move', '+DM', '-DM', 'TR', '+DI', '-DI', 'DX']