Automatic text categorization is the operation of sorting out the text documents into pre-
defined text categories using some machine learning algorithms. Normally, it defines the …

Feature Selection (FS) methods alleviate key problems in classification procedures as they
are used to improve classification accuracy, reduce data dimensionality, and remove …

Abstract Recent advancements in Information Technology (IT) have engendered the rapid
production of big data, as enormous volumes of data with high dimensional features grow …

Aiming at reducing data dimensionality, feature selection (FS) could improve the accuracy
and reduce computational cost of machine learning model, especially those with high …

A non-destructive technique should be developed for performance analysis of mango fruits
because the spongy tissue or internal defects could lower the quality of mango fruit and …

Feature selection is employed to reduce the feature dimensions and computational
complexity by eliminating irrelevant and redundant features. A vast amount of increasing …

Parkinson's disease (PD), which is a slowly progressing neurodegenerative disorder,
negatively affects people's daily lives. Early diagnosis is of great importance to minimize the …

Text documents usually contain high dimensional non-discriminative (irrelevant and noisy)
terms which lead to steep computational costs and poor learning performance of text …

Text representation is one kind of hot topics which support text classification (TC) tasks. It
has a substantial impact on the performance of TC. Although the most famous TF–IDF is …

With the advancement of technologies in the big data field, feature selection plays a vital role
in most of the prediction problems and many application domains including healthcare …