Two hybrid wrapper-filter feature selection algorithms applied to high-dimensional microarray experiments
We propose two new, simple, and efficient Hybrid Feature Selection techniques. We use a feature-based ranking to initialize the Binary Differential Evolution. We also propose a new fitness function influenced by the features in the population. Several statistical tests show the robustness and effectiveness of the proposals. The reducing of the size of the original set of features is larger than 99%.
microarray hybrid feature selection binary differential evolution high-dimensional data set