Feature selection has been an important issue in machine learning and data mining, and is
unavoidable when confronting with high‐dimensional data. With the advent of multilabel …

Hate speech and abusive language spreading on social media need to be detected
automatically to avoid conflict between citizen. Moreover, hate speech has a target …

Exponential growth of biomedical literature and clinical data demands more robust yet
precise computational methodologies to extract useful insights from biomedical literature …

In multi-label data, each instance is associated with a set of labels, instead of one label.
Similar to single-label data, feature selection plays an important role in improving …

Comprehensive monitoring of perfluoroalkyl and polyfluoroalkyl substances (PFASs) is
challenging because of the high analytical cost and an increasing number of analytes. We …

The ability to classify drones using radar signals is a problem of great interest. In this paper,
we apply convolutional neural networks (CNNs) to the Short-Time Fourier Transform (STFT) …

Background Early diagnosis for the diabetes complications is clinically demanding with
great significancy. Regarding the complexity of diabetes complications, we applied a multi …

Lack of planning when changing requirements to reflect stakeholders' expectations can lead
to propagated changes that can cause project failures. Existing tools cannot provide the …

Featured Application As students are usually characterized by more than one learning style,
multi-label classification methods may be applied for the diagnosis of a composite students' …

Hate speech and abusive words spread widely on social media. The impact of hate speech
on social media is hazardous, which can lead to discrimination, social conflict, and even …