Fuzzy rough entropy established in the notion of fuzzy rough set theory, which has been
effectively and efficiently applied for feature selection to handle the uncertainty in real …

Protein structure prediction is one of the important aspects while dealing with critical
diseases. An early prediction of protein folding helps in clinical diagnosis. In recent years …

As financial markets grow increasingly complex and dynamic, accurately predicting stock
price trends becomes crucial for investors and financial analysts. Effectively identifying and …

Fuzzy rough set approaches have received widespread attention across the disciplines of
feature selection and rule extraction. When calculating the fuzzy degree of membership of a …

Investor sentiment contagion has a profound influence on economic and social
development. This paper explores the diverse influences of various investor sentiments in …

Feature selection (FS) is an important data pre-processing technique in classification. It aims
to remove redundant and irrelevant features from the data, which reduces the dimensionality …

Feature selection is a fundamental application of rough set theory in identifying significant
features and reducing data dimensionality. For ordered data (OD), existing studies of feature …

Unsupervised feature selection (UFS), which involves selecting representative features from
unlabeled high-dimensional data, has attracted much attention. Numerous self …

The evaluation of the natural quality of cultivated land is crucial for preserving arable land
and achieving a balance between the quantity and quality of arable land. Therefore, a timely …