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  • Change detection in categorical evolving data streams

    Ienco, Dino; Bifet, Albert; Pfahringer, Bernhard; Poncelet, Pascal (ACM, 2014)
    Detecting change in evolving data streams is a central issue for accurate adaptive learning. In real world applications, data streams have categorical features, and changes induced in the data distribution of these categorical ...
  • Clustering based active learning for evolving data streams

    Ienco, Dino; Bifet, Albert; Žliobaitė, Indrė; Pfahringer, Bernhard (Springer, 2013)
    Data labeling is an expensive and time-consuming task. Choosing which labels to use is increasingly becoming important. In the active learning setting, a classifier is trained by asking for labels for only a small fraction ...

Dino Ienco has 4 co-authors in Research Commons.