Zohre Sadeghian - Department of Computer Engineering, Sari Branch, Islamic Azad University, Sari, Iran
Ebrahim Akbari - Department of Computer Engineering, Sari Branch, Islamic Azad University, Sari, Iran
Hossein Nematzadeh - Department of Computer Engineering, Sari Branch, Islamic Azad University, Sari, Iran
Homayun Motameni - Department of Computer Engineering, Sari Branch, Islamic Azad University, Sari, Iran

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 ۲۰۱۸ to ۲۰۲۱ 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.

Data dimension reduction, Classification, Feature Selection, Optimization algorithm, Meta-Heuristic Algorithms