Update README.md

README.md

@@ -41,7 +41,7 @@ The goal is to forecast future stock values and evaluate which approach generali
 | Model | RMSE      | MAPE     |
 |-------|-----------|----------|
 | ARIMA | 15.7959   | 0.0857   |
-| LSTM  | 5.6571    | 0.0302   |
+| LSTM  | 5.8747    | 0.0305   |
 
 **Conclusion:** LSTM significantly outperforms ARIMA with lower RMSE and MAPE, showing its ability to capture nonlinear patterns in stock prices. Under a single split, LSTM significantly outperforms ARIMA.
 
@@ -50,7 +50,7 @@ The goal is to forecast future stock values and evaluate which approach generali
 ### Rolling Window Evaluation
 | Model | RMSE (avg) | MAPE (avg) |
 |-------|------------|------------|
-| ARIMA (Rolling Window) | 3.448 | 0.0304 |
+| ARIMA (Rolling Window) | 3.448  | 0.0304 |
 | LSTM (Rolling Window)  | 23.282 | 0.1869 |
 
 Under rolling window evaluation, **ARIMA outperforms LSTM**, showing better stability and adaptability across multiple forecasting horizons.