Feature selection has become an indispensable machine learning process for data
preprocessing due to the ever-increasing sizes in actual data. There have been many …

Feature selection is a critical and prominent task in machine learning. To reduce the
dimension of the feature set while maintaining the accuracy of the performance is the main …

Feature selection is a required preprocess stage in most of the data mining tasks. This paper
presents an improved Harris hawks optimization (HHO) to find high-quality solutions for …

Many fields such as data science, data mining suffered from the rapid growth of data volume
and high data dimensionality. The main problems which are faced by these fields include …

In data mining and machine learning, feature selection is a critical part of the process of
selecting the optimal subset of features based on the target data. There are 2n potential …

Searching for the (near) optimal subset of features is a challenging problem in the process of
feature selection (FS). In the literature, Swarm Intelligence (SI) algorithms show superior …

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) is a machine learning process commonly used to reduce the high
dimensionality problems of datasets. This task permits to extract the most representative …

With the explosion of data generation, getting optimal solutions to data driven problems is
increasingly becoming a challenge, if not impossible. It is increasingly being recognised that …

Swarm intelligence (SI), an integral part in the field of artificial intelligence, is gradually
gaining prominence, as more and more high complexity problems require solutions which …