Feature selection plays an important role in the machine-vision-based online detection of
foreign fibers in cotton because of improvement detection accuracy and speed. Feature sets …

Multi-label learning deals with data belonging to different labels simultaneously. Like
traditional supervised feature selection, multi-label feature selection also plays an important …

Feature selection is a significant task for data mining and pattern recognition. It aims to
select the optimal feature subset with the minimum redundancy and the maximum …

Intrusion detection systems (IDSs) play an important role in the security of computer
networks. One of the main challenges in IDSs is the high-dimensional input data analysis …

We introduce a new approach for learning forecasting models over large multi-sensor data
sets, including the steps of sliding-window-based feature extraction and rough-set-inspired …

Background Up to half of patients with dementia may not receive a formal diagnosis, limiting
access to appropriate services. It is hypothesised that it may be possible to identify …

Image fingerprinting is a technique that summarizes the perceptual characteristics of a
digital image into an invariant digest, and it is one of the most effective solutions for digital …

Multilabel learning has a wide range of potential applications in reality. It attracts a great
deal of attention during the past years and has been extensively studied in many fields …

The task of feature selection is crucial for constructing prediction and classification models,
resulting in their higher quality and interpretability. However, it is often neglected that some …

Text Classification (TC) is the process of assigning several different categories to a set of
texts. This study aims to evaluate the state of the arts of TC studies. Firstly, TC-related …