Deep learning (DL) is gaining significant prevalence in every field of study due to its
domination in training large data sets. However, several applications are utilizing machine …

Cardiovascular disease is the leading cause of global mortality and responsible for millions
of deaths annually. The mortality rate and overall consequences of cardiac disease can be …

Hyper-heuristics is a fairly recent technique that aims at effectively solving various real-world
optimization problems. This is the first book on hyper-heuristics, and aims to bring together …

The induction of decision trees is a widely-used approach to build classification models that
guarantee high performance and expressiveness. Since a recursive-partitioning strategy …

Due to the development of biomedical equipment and healthcare level, especially in the
Intensive Care Unit (ICU), a considerable amount of data has been collected for analysis …

Ensemble pruning aims to achieve a good result in classification using a smaller size of
classifiers by finding the optimal sub-ensemble. Diversity and accuracy of classifiers are …

A Meta-evolutionary Selection of Constituents in Ensemble DE (MeSCEDE) framework is
proposed in this paper to automate the design of high-level multi-population ensemble …

Hybrid metaheuristics have proven to be effective at solving complex real-world problems.
However, designing hybrid metaheuristics is extremely time consuming and requires expert …

Abstract One-Class Classification (OCC) corresponds to a subclass of unsupervised
Machine Learning (ML) that is valuable when labeled data is non-existent. In this paper, we …

As the artificial floating bed (AFB) is more extensively applied in water treatment, the
hydraulic characteristics of the AFB has been broadly investigated. However, the …