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Optimizing Gated Recurrent Unit (GRU) For Gold Price Prediction: Hyperparameter Tuning and Model Evaluation On Historical XAU/USD Data by aslopez is a document available to read on EtoBox.
This study explores the optimization of a Gated Recurrent Unit (GRU) model for predicting daily gold prices (XAU/USD) by tuning hyperparameters through various configurations. The optimal model achieved a Mean Absolute Error (MAE) of 25.76, Mean Squared Error (MSE) of 954.97, and Root Mean Squared Error (RMSE) of 30.90, indicating its potential effectiveness for financial decision-making. The research highlights the need for further enhancements by incorporating external factors and advanced model architect
- Author
- aslopez
- Language
- EN