Feature selection has become an indispensable machine learning process for data
preprocessing due to the ever-increasing sizes in actual data. There have been many …

Feature selection is a critical and prominent task in machine learning. To reduce the
dimension of the feature set while maintaining the accuracy of the performance is the main …

In December 2019, a novel coronavirus, called COVID-19, was discovered in Wuhan, China,
and has spread to different cities in China as well as to 24 other countries. The number of …

Searching for the (near) optimal subset of features is a challenging problem in the process of
feature selection (FS). In the literature, Swarm Intelligence (SI) algorithms show superior …

Metaheuristic algorithms are computational intelligence paradigms especially used for
sophisticated solving optimization problems. This chapter aims to review of all …

The main objective of feature selection is to improve learning performance by selecting
concise and informative feature subsets, which presents a challenging task for machine …

Harris hawk optimization (HHO) is one of the recently proposed metaheuristic algorithms
that has proven to be work more effectively in several challenging optimization tasks …

In the feature selection process, reaching the best subset of features is considered a difficult
task. To deal with the complexity associated with this problem, a sophisticated and robust …

Optimization algorithms have shown significant advantages in solving diverse several real-
world problems, especially where are limitations in computations and hardware …

Whale optimization algorithm is one of the recent nature-inspired optimization technique
based on the behavior of bubble-net hunting strategy. In this paper, a novel binary version of …