Evolutionary Feature Selection for Time-Series Forecasting
María Lourdes Linares-Barrera, M. J. Jiménez-Navarro, Isabel Sofía Brito, José C. Riquelme, M. Martínez-Ballesteros · 2024
In machine learning, feature selection is crucial for pinpointing the key subset of features that enhances interpretability and preserves or boosts the model's original performance. Filter methods, which assess features using statistical metrics, are particularly notable. Recently, a novel metric called Conditional Dependence Coefficient has been proposed to measure the dependence between subsets of variables.