A data stream is a potentially uninterrupted flow of data. Mining this flow makes it necessary to cope with uncertainty, as only a part of the stream can be stored. In this pape...
Pierre-Alain Laur, Richard Nock, Jean-Emile Sympho...
Probabilistic mixture models are used for a broad range of data analysis tasks such as clustering, classification, predictive modeling, etc. Due to their inherent probabilistic na...
Most data mining algorithms assume static behavior of the incoming data. In the real world, the situation is different and most continuously collected data streams are generated by...
Lior Cohen, Gil Avrahami, Mark Last, Abraham Kande...
In realistic settings the prevalence of a class may change after a classifier is induced and this will degrade the performance of the classifier. Further complicating this scenari...
Data streams are usually generated in an online fashion characterized by huge volume, rapid unpredictable rates, and fast changing data characteristics. It has been hence recogniz...
Xuan Hong Dang, Wee Keong Ng, Kok-Leong Ong, Vince...