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 …

Disease diagnosis and prediction methods in biotechnology and medicine have significantly
advanced over time. Consequently, analyzing raw gene expression is crucial for identifying …

Feature selection (FS) aims to eliminate redundant features and choose the informative
ones. Since labeled data are not always easily available and abundant unlabeled data are …

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 …

Feature selection, an optimization problem, becomes an important pre-process tool in data
mining, which simultaneously aims at minimizing feature-size and maximizing model …

Continuous ant colony optimization was a population-based heuristic search algorithm
inspired by the pathfinding behavior of ant colonies with a simple structure and few control …

There is a new nature-inspired algorithm called salp swarm algorithm (SSA), due to its
simple framework, it has been widely used in many fields. But when handling some …

Cyber-attacks and unauthorized application usage have increased due to the extensive use
of Internet services and applications over computer networks, posing a threat to the service's …

Nowadays, people use smart devices everywhere and for different applications such as
healthcare. The Internet of Healthcare Things (IoHT) generates enormous amounts of data …

The recent advancements in science, engineering, and technology have facilitated huge
generation of datasets. These huge datasets contain noisy, redundant, and irrelevant …