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Genetic Algorighm Representation Selection Impact On Binary Classification Problems, Stephen V. Maldonado
Genetic Algorighm Representation Selection Impact On Binary Classification Problems, Stephen V. Maldonado
Honors Undergraduate Theses
In this thesis, we explore the impact of problem representation on the ability for the genetic algorithms (GA) to evolve a binary prediction model to predict whether a physical therapist is paid above or below the median amount from Medicare. We explore three different problem representations, the vector GA (VGA), the binary GA (BGA), and the proportional GA (PGA). We find that all three representations can produce models with high accuracy and low loss that are better than Scikit-Learn’s logistic regression model and that all three representations select the same features; however, the PGA representation tends to create lower weights …