Novelty detection in data streams is the task of detecting concepts that were not known prior,
in streams of data. Many machine learning algorithms have been proposed to detect these …

Wearable biosensors represent an opportunity to improve treatment and research into a
variety of diseases, including substance use disorder. They provide continuous, real-time …

Multi-label data streams are sequences of multi-label instances arriving over time to a multi-
label classifier. The properties of the stream may continuously change due to concept drift …

Drifting data streams and multi-label data are both challenging problems. Multi-label
instances may simultaneously be associated with many labels and classifiers must predict …

Dynamic data streams applications are bound to potential changes in data distribution, of
which in the context of data stream mining, will cause concept drift. Data stream mining …

Due to an ever-increasing demand for analyzing the large volumes of information issuing
from high-speed data streams, multi-label stream classification is replacing the traditional …

Available works addressing multi-label classification in a data stream environment focus on
proposing accurate prediction models; however, they struggle to balance effectiveness and …