Machine learning has shown utility in detecting patterns within large, unstructured, and
complex datasets. One of the promising applications of machine learning is in precision …

Affective computing, a subcategory of artificial intelligence, detects, processes, interprets,
and mimics human emotions. Thanks to the continued advancement of portable non …

Feature selection is widely used in various fields as a key means of data dimension
reduction. The existing feature selection algorithms only use one linear or nonlinear …

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 …

Explainability has become one of the most discussed topics in machine learning research in
recent years, and although a lot of methodologies that try to provide explanations to black …

Feature selection is an important preprocessing process in machine learning. It selects the
crucial features by removing irrelevant features or redundant features from the original …

Nowadays, being in digital era the data generated by various applications are increasing
drastically both row-wise and column wise; this creates a bottleneck for analytics and also …

The rapid growth of e-commerce has increased the need for retailers to understand and
predict customer satisfaction to support data-driven managerial decisions. This study …

High-dimensional data analysis is a challenge for researchers and engineers in the fields of
machine learning and data mining. Feature selection provides an effective way to solve this …

Fighting Earth's degradation and safeguarding the environment are subjects of topical
interest and sources of hot debate in today's society. According to the United Nations, there …