Feature Selection Methods for Machine Learning Algorithms like SVR: Implementing Filter and Wrapper Approaches
Implementation of feature selection techniques for SVR machine learning algorithms, featuring one filter-based method (CFS Correlation-based Feature Selection) and two wrapper methods (Genetic Algorithm GA and Particle Swarm Optimization PSO). The gridsearch module performs hyperparameter tuning for SVR optimization, while SVM_CV handles k-fold cross-validation procedures with customizable parameters.