Classification and Adaptive Novel Class Detection of Feature-Evolving Data Streams
Classification and Adaptive Novel Class Detection of Feature-Evolving Data Streams is a scholarly work, published in 2013 in ''IEEE Transactions on Knowledge and Data Engineering''. The main subjects of the publication include computer science, artificial intelligence, feature, concept drift, classifier, data mining, anomaly detection, pattern recognition, class, intrusion detection system, machine learning, one-class classification, data stream, and data stream mining. The authors propose an ensemble classification framework, where each classifier is equipped with a novel class detector, to address concept-drift and concept-evolution.