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

Data visualization is a key tool in data mining for understanding big datasets. Many
visualization methods have been proposed, including the well-regarded state-of-the-art …

Clustering is a difficult and widely studied data mining task, with many varieties of clustering
algorithms proposed in the literature. Nearly all algorithms use a similarity measure such as …

Manifold learning (MaL) methods are an invaluable tool in today's world of increasingly
huge datasets. MaL algorithms can discover a much lower-dimensional representation …

In this paper, an Improved version of the Multi-Trial Vector-based Differential Evolution
(IMTDE) algorithm is proposed and adapted for clustering data. The purpose here is to …

Recently, feature selection has become an increasingly important area of research due to
the surge in high-dimensional datasets in all areas of modern life. A plethora of feature …

Symbolic regression plays a crucial role in machine learning and data science by allowing
the extraction of meaningful mathematical models directly from data without imposing a …

Clustering is the process of grou** related instances of unlabelled data into distinct
subsets called clusters. While there are many different clustering methods available, almost …

Unsupervised learning is a fundamental category of machine learning that works on data for
which no pre-existing labels are available. Unlike in supervised learning, which has such …

Abstract Cartesian Genetic Programming (CGP) is a type of Genetic Programming, which
uses a sequence of integers to represent an executable graph structure. The most common …