Abstract
Diabetes Mellitus is the one of the most serious health challenges. During the last 20 years the total number of diabetes patients has risen from 30 million to 230 million. It is a major health problem worldwide. So there is need of predictive model for early and accurate detection of diabetes. Diabetes disease diagnosis with proper interpretation of the diabetes data is an important classification problem. This research work proposes a Classifier for detection of Diabetes using Genetic programming (GP). Classification expression evaluation is used for creation of classifier. Reduced function pool of just arithmetic operators is used which allows for lesser validation and leniency during crossover and mutation.
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Pradhan, M., Bamnote, G.R. (2015). Design of Classifier for Detection of Diabetes Mellitus Using Genetic Programming. In: Satapathy, S., Biswal, B., Udgata, S., Mandal, J. (eds) Proceedings of the 3rd International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA) 2014. Advances in Intelligent Systems and Computing, vol 327. Springer, Cham. https://doi.org/10.1007/978-3-319-11933-5_86
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DOI: https://doi.org/10.1007/978-3-319-11933-5_86
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-11932-8
Online ISBN: 978-3-319-11933-5
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