Fix: Correct Profit Factor calculation and display units in AI Learning

Backend changes (logger/decision_logger.go):
- Fixed Profit Factor to use standard formula (total profit / total loss)
- Previously used average values which was incorrect when win/loss counts differ
- Now saves total amounts before calculating averages for accurate ratio
Frontend changes (web/src/components/AILearning.tsx):
- Fixed display units: changed USDT amounts from "%" to "USDT"
- Updated avg_win and avg_loss to show "USDT Average" instead of "%"
- Updated best/worst performer displays to show "USDT" instead of "%"
- Added "(USDT)" labels to table headers for clarity
- Removed "%" from all table data cells showing monetary amounts
This ensures accurate performance metrics and eliminates user confusion
between percentage values and absolute USDT amounts.
Co-Authored-By: tinkle-community <tinklefund@gmail.com>

logger/decision_logger.go

@@ -429,6 +429,10 @@ func (l *DecisionLogger) AnalyzePerformance(lookbackCycles int) (*PerformanceAna
 	if analysis.TotalTrades > 0 {
 		analysis.WinRate = (float64(analysis.WinningTrades) / float64(analysis.TotalTrades)) * 100
 
+		// 计算总盈利和总亏损
+		totalWinAmount := analysis.AvgWin   // 当前是累加的总和
+		totalLossAmount := analysis.AvgLoss // 当前是累加的总和（负数）
+
 		if analysis.WinningTrades > 0 {
 			analysis.AvgWin /= float64(analysis.WinningTrades)
 		}
@@ -436,8 +440,10 @@ func (l *DecisionLogger) AnalyzePerformance(lookbackCycles int) (*PerformanceAna
 			analysis.AvgLoss /= float64(analysis.LosingTrades)
 		}
 
-		if analysis.AvgLoss != 0 {
-			analysis.ProfitFactor = analysis.AvgWin / (-analysis.AvgLoss)
+		// Profit Factor = 总盈利 / 总亏损（绝对值）
+		// 注意：totalLossAmount 是负数，所以取负号得到绝对值
+		if totalLossAmount != 0 {
+			analysis.ProfitFactor = totalWinAmount / (-totalLossAmount)
 		}
 	}