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

Abstract Recent advancements in Information Technology (IT) have engendered the rapid
production of big data, as enormous volumes of data with high dimensional features grow …

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 …

When learning from high-dimensional data for symbolic regression (SR), genetic
programming (GP) typically could not generalize well. Feature selection, as a data …

Feature construction and feature selection are two common pre-processing methods for
classification. Genetic Programming (GP) can be used to solve feature construction and …

High dimensionality, also known as the curse of dimensionality, is still a major challenge for
automatic classification solutions. Accordingly, several feature selection (FS) strategies have …

Biomedical and bioinformatics datasets are generally large in terms of their number of
features-and include redundant and irrelevant features, which affect the effectiveness and …

Feature Selection (FS) is an important pre-processing step in machine learning and it
reduces the number of features/variables used to describe each member of a dataset. Such …

Modern genetic programming (GP) operates within the statistical machine learning (SML)
framework. In this framework, evolution needs to balance between approximation of an …

Feature selection is a data processing method which aims to select effective feature subsets
from original features. Feature selection based on evolutionary computation (EC) algorithms …