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 and classification have previously been widely applied in various areas
like business, medical and media fields. High dimensionality in datasets is one of the main …

Abstract The popularity of Contrastive Language-Image Pre-training (CLIP) has propelled its
application to diverse downstream vision tasks. To improve its capacity on downstream …

Explainable artificial intelligence is an emerging research direction helping the user or
developer of machine learning models understand why models behave the way they do …

Feature selection is one of the most fundamental problems in machine learning and has
drawn increasing attention due to high-dimensional data sets emerging from different fields …

Feature selection is a preprocessing technique that identifies the key features of a given
problem. It has traditionally been applied in a wide range of problems that include biological …

Deep learning on graphs has become one of the hottest topics in machine learning. The
book consists of four parts to best accommodate our readers with diverse backgrounds and …

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 …

State of health (SOH) is a key parameter to assess lithium-ion battery feasibility for
secondary usage applications. SOH estimation based on machine learning has attracted …