A Review of Feature Selection Method Based on Optimization Algorithms

Journal of Computer & Robotics

مقاله 5، دوره 16، شماره 1 - شماره پیاپی 27، فروردین 2023، صفحه 57-74   

نوع مقاله: Reviews

شناسه دیجیتال (DOI): 10.22094/jcr.2022.1974681.1286

نویسندگان

Zohre Sadeghian؛ Ebrahim Akbari^* ؛ Hossein Nematzadeh؛ Homayun Motameni

Department of Computer Engineering, Sari Branch, Islamic Azad University, Sari, Iran

چکیده

Feature selection is the process of identifying relevant features and removing irrelevant and repetitive features with the aim of observing a subset of features that describe the problem well and with minimal loss of efficiency. One of the feature selection approaches is using optimization algorithms. This work provides a summary of some meta-heuristic feature selection methods proposed from 2018 to 2021 that were designed and implemented on a wide range of different data. The results of the study showed that some meta-heuristic algorithms alone cannot perfectly solve the feature selection problem on all types of datasets with an acceptable speed. In other words, depending on dataset, a special meta-heuristic algorithm should be used.

کلیدواژه‌ها

Data dimension reduction؛ Classification؛ Feature Selection؛ Optimization Algorithm؛ Meta-heuristic Algorithms