A Review of Feature Selection Method Based on Optimization Algorithms

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.

کلیدواژه ها:

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