Particle swarm optimization (PSO) is one of the most well-regarded swarm-based algorithms
in the literature. Although the original PSO has shown good optimization performance, it still …

Feature selection has gained much consideration from scholars working in the domain of
machine learning and data mining in recent years. Feature selection is a popular problem in …

The whale optimization algorithm (WOA) is a prominent problem solver which is broadly
applied to solve NP-hard problems such as feature selection. However, it and most of its …

The shuffled frog leaping algorithm is a new optimization algorithm proposed to solve the
combinatorial optimization problem, which effectively combines the memetic algorithm …

One of the major problems in Big Data is a large number of features or dimensions, which
causes the issue of “the curse of dimensionality” when applying machine learning …

Feature selection (FS) is an important data processing technique in the field of machine
learning. There have been various FS methods, but all assume that the cost associated with …

Feature selection is an important task in data mining and machine learning to reduce the
dimensionality of the data and increase the performance of an algorithm, such as a …

Feature selection is an essential step in various tasks, where filter feature selection
algorithms are increasingly attractive due to their simplicity and fast speed. A common filter …

Feature selection has two major conflicting aims, ie, to maximize the classification
performance and to minimize the number of selected features to overcome the curse of …

Artificial intelligence (AI) emphasises the creation of intelligent machines/systems that
function like humans. AI has been applied to many real-world applications. Machine …