Emotion recognition technology through analyzing the EEG signal is currently an essential
concept in Artificial Intelligence and holds great potential in emotional health care, human …

Abstract Chronic Disease Prediction plays a pivotal role in healthcare informatics. It is crucial
to diagnose the disease at an early stage. This paper presents a survey on the utilization of …

Hands-on Machine Learning with R provides a practical and applied approach to learning
and develo** intuition into today's most popular machine learning methods. This book …

Background Support vector machines (SVM) are a powerful tool to analyze data with a
number of predictors approximately equal or larger than the number of observations …

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 …

A major limitation of fuzzy or neuro-fuzzy systems is their failure to deal with high-
dimensional datasets. This happens primarily due to the use of T-norm, particularly, product …

Recognizing cross-subject emotions based on brain imaging data, eg, EEG, has always
been difficult due to the poor generalizability of features across subjects. Thus …

In classification, regression, and other data mining applications, feature selection (FS) is an
important pre-process step which helps avoid advert effect of noisy, misleading, and …

Financial credit scoring is one of the most crucial processes in the finance industry sector to
be able to assess the credit-worthiness of individuals and enterprises. Various statistics …

In an actual industrial scenario, machines typically operate normally for the majority of the
time, with malfunctions occurring only occasionally. As a result, there is very little recorded …