A Feature Selection Algorithm Using Energy Based Learning In Pure Mql5

This article discusses the implementation of a feature selection algorithm, FREL, which utilizes regularized energy-based learning and feature weighting to improve accuracy and stability in algorithmic trading. The authors provide an overview of the theoretical foundations and demonstrate the effectiveness of the approach through an example MQL5 program.