Ali Algarni1, Mahmoud Ragab2,3,4,*, Wardah Alamri5, Samih M. Mostafa6
Computer Systems Science and Engineering, Vol.42, No.1, pp. 303-318, 2022, DOI:10.32604/csse.2022.022152
Abstract The accuracy of the statistical learning model depends on the learning technique used which in turn depends on the dataset’s values. In most research studies, the existence of missing values (MVs) is a vital problem. In addition, any dataset with MVs cannot be used for further analysis or with any data driven tool especially when the percentage of MVs are high. In this paper, the authors propose a novel algorithm for dealing with MVs depending on the feature selection (FS) of similarity classifier with fuzzy entropy measure. The proposed algorithm imputes MVs in cumulative order. The candidate feature to be… More >
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