Abstract
In this research work, we consider the diabetes classification on PIMA Indian dataset with Fuzzy Genetic Algorithm. We applied two algorithms consisting of Fuzzy Algorithm and Genetic Algorithm to combine the process to enhance the classification performance. In addition, we used Synthetic Minority Over-sampling Technique (SMOTE) to handle the imbalance data set. We conducted the experiments and found out that 5-fold cross-validation is the suitable approach, providing very good results compared with those obtained from other techniques.
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Thungrut, W., Wattanapongsakorn, N. (2019). Diabetes Classification with Fuzzy Genetic Algorithm. In: Unger, H., Sodsee, S., Meesad, P. (eds) Recent Advances in Information and Communication Technology 2018. IC2IT 2018. Advances in Intelligent Systems and Computing, vol 769. Springer, Cham. https://doi.org/10.1007/978-3-319-93692-5_11
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DOI: https://doi.org/10.1007/978-3-319-93692-5_11
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