A meta-heuristic feature selection algorithm combining random sampling accelerator and ensemble using data perturbation

Meta-heuristic algorithms have been extensively utilized in feature selection tasks because they can obtain the global optimal solution. However, the meta-heuristic algorithm will take too much time in the face of a large number of samples. Although most of the studies compromise to approximate opti...

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