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Combining Multiple Features for Product Categorisation by Multiple Kernel Learning Read chapter Read first chapter

2019 | OriginalPaper | Chapter

Diabetes Classification with Fuzzy Genetic Algorithm

Authors : Wissanu Thungrut, Naruemon Wattanapongsakorn

Published in: Recent Advances in Information and Communication Technology 2018

Publisher: Springer International Publishing

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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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previous chapter Robust Kurtosis Projection Approach for Mangrove Classification
next chapter Decision Fusion Using Fuzzy Dempster-Shafer Theory
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Metadata
Title
Diabetes Classification with Fuzzy Genetic Algorithm
Authors
Wissanu Thungrut
Naruemon Wattanapongsakorn
Copyright Year
2019
Book
Recent Advances in Information and Communication Technology 2018

Print ISBN: 978-3-319-93691-8

Electronic ISBN: 978-3-319-93692-5

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-3-319-93692-5_11

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