This survey is an effort to provide a research repository and a useful reference for
researchers to guide them when planning to develop new Nature-inspired Algorithms …

Feature selection (FS) represents an optimization problem that aims to simplify and improve
the quality of highly dimensional datasets through selecting prominent features and …

In the recent decades, researchers have introduced an abundance of feature selection
methods many of which are studied and analyzed over the high dimensional datasets …

This paper presents modified versions of a recent swarm intelligence algorithm called Harris
hawks optimization (HHO) via incorporating genetic operators (crossover and mutation CM) …

In this paper, we propose a generalized wrapper-based feature selection, called GeFeS,
which is based on a parallel new intelligent genetic algorithm (GA). The proposed GeFeS …

In the past several single classifiers, homogeneous and heterogeneous ensembles have
been proposed to detect the customers who are most likely to churn. Despite the popularity …

High dimensionality is one of the main challenges in Quantitative Structure-Activity
Relationship (QSAR) classification modeling, and feature selection as an effective …

The microarrays permit experts to monitor the gene profiling for thousands of genes across
an array of cellular responses, phenotype, and circumstances. Selecting a tiny subset of …

In recent years, medical data analysis has become paramount in delivering accurate
diagnoses for various diseases. The plethora of medical data sources, encompassing …

DNA microarray data is expected to be a great help in the development of efficient diagnosis
and tumor classification. However, due to the small number of instances compared to a large …