Ensemble representation learning: an analysis of fitness and survival for wrapper-based genetic programming methods

Recently we proposed a general, ensemble-based feature engineering wrapper (FEW) that was paired with a number of machine learning methods to solve regression problems. Here, we adapt FEW for supervised classification and perform a thorough analysis of fitness and survival methods within this framework... (read more)

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