Selecting relevant feature subsets is vital in machine learning, and multiclass feature
selection is harder to perform since most classifications are binary. The feature selection …

The main objective of feature selection is to improve learning performance by selecting
concise and informative feature subsets, which presents a challenging task for machine …

Several feature selection methods have been developed to extract the optimal features from
a dataset in medical datasets classification. Creating an efficient technique has become a …

Feature selection (FS) is a popular data pre-processing technique in machine learning to
extract the optimal features to maintain or increase the classification accuracy of the dataset …

There have been many algorithms created and introduced in the literature inspired by
various events observable in nature, such as evolutionary phenomena, the actions of social …

The problem of feature selection involves selecting the most informative subset of features
from a data item which have the most impact in the context of classification. It is an …

Swarm intelligence algorithms can efficiently solve feature selection optimization problems
for classification, and their classification performance is also excellent. The Sparrow Search …

Security has been one of the important problems in the processing, storage and
transmission of information. The transfer of information to virtual environments with …

With the rapid expansion in Biological Sciences, biomedical data classification has become
challenging. These datasets generally consist of missing values, redundant features and …

Speech emotion recognition and its precise classification are challenging tasks that heavily
depend on the quality of feature extraction and selection for speech signals. Many feature …