Ai Huong, Penny Ngu and Hamid, Hashibah (2023) Systematic Literature Review of Mixed Variables Classification. International Journal of Data Science and Advanced Analytics, 5 (5). pp. 184-192. ISSN 2563-4429

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Abstract

Classification is one of the most popular approaches that had been used in a variety of fields. There are a lot of classification methods that are applicable to classify objects into their respective groups. Among the classification methods, the location model and smoothed location model received attention when the data consists of mixed continuous and categorical variables. In this paper, classification, location model and smoothed location model are screened from the Scopus and Science Direct websites for review purposes. A total of 70 articles were chosen through the systematic review processes based on the related studies’ topics. The studies had been reviewed and discussed under the topic of classification, location model and smoothed location model in different data situations. The systematic literature review has many benefits compared to traditional literature review. The systematic review process is able to provide a defined review process and fundamental priorities that can manage research bias easily. Based on the reviews, smoothed location model outperforms the other classification techniques in terms of classification performance. However, there are not many articles that particularly discuss the application of the location model and smoothed location model in mixed variables classification. Therefore, smoothed location model is suggested to be considered in the future work for mixed variables classification situation

Item Type:	Article
Uncontrolled Keywords:	Classification; location model; smoothed location model; systematic literature review
Subjects:	Q Science > QA Mathematics
Divisions:	School of Quantitative Sciences
Depositing User:	Mdm. Sarkina Mat Saad @ Shaari
Date Deposited:	29 May 2024 10:24
Last Modified:	29 May 2024 10:24
URI:	https://repo.uum.edu.my/id/eprint/30819

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