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• W4295030847 abstract "Abstract Diabetes Mellitus (DM) is one of the most significant chronic diseases owing to its prevalence, economic and social consequences, and poor influence on the quality of life of those affected by it. According to World Health Organisation in 1980, there were 108 million diabetics. Worldwide diabetes Mellitus increased to 422 million by 2014. By 2045, diabetes is expected to affect 700 million individuals globally, estimated to the International Diabetes Federation of 2021 [1] In this study, a new metaheuristic algorithm Modified Binary Multi Neighborhood Artificial Bee Colony (MBMNABC) algorithm has been developed for feature selection and compared the results with traditional Binary Multi Neighborhood Artificial Bee Colony (BMNABC) as well as previous research works. The results show that the swarm-based meta-heuristic algorithm Modified Binary Multi Neighborhood Artificial Bee Colony (BMNABC) gives an acceptable result compared of traditional feature selection algorithm. The features selected by the Modified Binary Multi Neighborhood Artificial Bee Colony (MBMNABC) algorithm and Binary Multi Neighborhood Artificial Bee Colony (BMNABC) algorithm has been compared with the features selected by the Expert selection. The proposed method selected relevant features as compared to traditional BMNABC algorithm and provided better results for the detection of diabetes. Five diabetes datasets have been used in this research, where the results each dataset have been compared with previous works. In order to train the datasets, all the five datasets were divided in the ratio of 70:30% split for the training set and test set respectively. Three machine learning algorithms, Rough Set, Random Forest, and Random Committee have been applied for classification. For validation 10-fold cross-validation was performed. The highest accuracy was achieved by Random Forest for both features methods Modified BMNABC algorithm, and traditional BMNABC algorithm respectively." @default.
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• W4295030847 date "2022-09-09" @default.
• W4295030847 modified "2023-09-27" @default.
• W4295030847 title "Feature Selection in Diabetes Data Using Modified Bmnabc Algorithm for Detection of Diabetes; a Comparison Between Traditional Bmnabc Algorithm" @default.
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• W4295030847 doi "https://doi.org/10.21203/rs.3.rs-2027618/v1" @default.
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