Curse of dimensionality is known as big challenges in data mining, pattern recognition,
computer vison and machine learning in recent years. Feature selection and feature …

The classification efficiency of majority classes for imbalanced data is so concerned in real-
world applications. Almost fuzzy neighborhood radius still needs to be manually set and …

With the extensive applicability of machine learning classification algorithms to a wide
spectrum of domains, feature selection (FS) becomes a relevant data preprocessing …

Fuzzy rough set theory can tackle feature redundancy in data and select more informative
features for machine learning tasks. Gaussian kernel is often coupled with fuzzy rough set …

The feature selection process plays an important role in different fields, particularly in
bioinformatics and microarray gene expression data analysis, for choosing discriminative …

In this paper, we are addressing the NP-hard nurse rostering problem utilizing a 2-stage
approach. In stage one, Monte Carlo Tree Search (MCTS) and Hill Climbing (HC) are …

Feature selection is a vital dimensionality reduction technology for machine learning and
data mining that aims to select a minimal subset from the original feature space. Traditional …

High dimensional datasets usually suffer from curse of dimensionality which may increase
the classification time and decrease the classification accuracy beyond a certain …

Accurate power load prediction plays a key role in reducing resource waste and ensuring
stable and safe operations of power systems. To address the problems of poor stability and …

It is wise to investigate past and present epidemics in the hopes of profiting from them and
being better prepared for future ones. COVID-19 is one of the most recent and well-known …