Over recent years, there has been a rapid development of deep learning (DL) in both
industry and academia fields. However, finding the optimal hyperparameters of a DL model …

Specialized data preparation techniques, ranging from data cleaning, outlier detection,
missing value imputation, feature selection (FS), amongst others, are procedures required to …

In the past decades, the rapid growth of computer and database technologies has led to the
rapid growth of large-scale datasets. On the other hand, data mining applications with high …

This article presents a comprehensively state-of-the-art investigation of the engineering
applications utilized by binary metaheuristic algorithms. Surveyed work is categorized based …

The massive growth of data in recent years has led challenges in data mining and machine
learning tasks. One of the major challenges is the selection of relevant features from the …

In the past decades, the rapid growth of computer and database technologies has led to the
rapid growth of large-scale medical datasets. On the other, medical applications with high …

Feature selection (FS), as one of the most significant preprocessing techniques in the fields
of machine learning and pattern recognition, has received great attention. In recent years …

Abstract Machine learning (ML), as the most promising paradigm to discover deep
knowledge from data, has been widely applied to practical applications, such as …

The high-dimensional datasets in various domains, such as text categorization, information
retrieval and bioinformatics, have highlighted the importance of feature selection in data …

A population-based optimizer called beluga whale optimization (BWO) depicts behavioral
patterns of water aerobics, foraging, and diving whales. BWO runs effectively, nevertheless it …