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 …

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 …

One of the major problems in Big Data is a large number of features or dimensions, which
causes the issue of “the curse of dimensionality” when applying machine learning …

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 …

Feature selection is an essential step in various tasks, where filter feature selection
algorithms are increasingly attractive due to their simplicity and fast speed. A common filter …

Enormous data growth in multiple domains has posed a great challenge for data processing
and analysis techniques. In particular, the traditional record maintenance strategy has been …

Feature selection (FS) in data mining is one of the most challenging and most important
activities in pattern recognition. In this article, a new hybrid model of whale optimization …

Feature selection is an important research area for big data analysis. In recent years, various
feature selection approaches have been developed, which can be divided into four …

Feature selection is a technique commonly used in Data Mining and Machine Learning.
Traditional feature selection methods, when applied to large datasets, generate a large …

Feature selection (FS) is considered as one of the most common and challenging tasks in
Machine Learning. FS can be considered as an optimization problem that requires an …