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 …

Differential evolution (DE) is a popular evolutionary algorithm inspired by Darwin's theory of
evolution and has been studied extensively to solve different areas of optimisation and …

In this paper, a novel swarm-based metaheuristic algorithm inspired from the behaviors of
beluga whales, called beluga whale optimization (BWO), is presented to solve optimization …

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 …

Selecting relevant feature subsets is vital in machine learning, and multiclass feature
selection is harder to perform since most classifications are binary. The feature selection …

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 …

In the past decades, the rapid growth of computer and database technologies has led to the
rapid growth of large-scale datasets. On the other hand, data mining applications with high …

Feature selection is an important data processing method to reduce dimension of the raw
datasets while preserving the information as much as possible. In this paper, an enhanced …

Cloud-fog computing frameworks are emerging paradigms developed to add benefits to the
current Internet of Things (IoT) architectures. In such frameworks, task scheduling plays a …

Feature selection is a required preprocess stage in most of the data mining tasks. This paper
presents an improved Harris hawks optimization (HHO) to find high-quality solutions for …