Research Commons

Browsing by Author "Bifet, Albert"

Research Commons

Browsing by Author "Bifet, Albert"

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  • Batch-incremental versus instance-incremental learning in dynamic and evolving data 
    Read, Jesse; Bifet, Albert; Pfahringer, Bernhard; Holmes, Geoffrey (Springer, 2012)
    Many real world problems involve the challenging context of data streams, where classifiers must be incremental: able to learn from a theoretically- infinite stream of examples using limited time and memory, while being ...
  • Clustering performance on evolving data streams: Assessing algorithms and evaluation measures within MOA 
    Kranen, Philipp; Kremer, Hardy; Jensen, Timm; Seidl, Thomas; Bifet, Albert; Homes, Geoff; Pfahringer, Bernhard (2010)
    In today's applications, evolving data streams are ubiquitous. Stream clustering algorithms were introduced to gain useful knowledge from these streams in real-time. The quality of the obtained clusterings, i.e. how good ...
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    Efficient multi-label classification for evolving data streams 
    Read, Jesse; Bifet, Albert; Holmes, Geoffrey; Pfahringer, Bernhard (University of Waikato, Department of Computer Science, 2010)
    Many real world problems involve data which can be considered as multi-label data streams. Efficient methods exist for multi-label classification in non streaming scenarios. However, learning in evolving streaming scenarios ...
  • Ensembles of restricted Hoeffding trees 
    Bifet, Albert; Frank, Eibe; Holmes, Geoffrey; Pfahringer, Bernhard (Association for Computing Machinery (ACM), 2012)
    The success of simple methods for classification shows that is is often not necessary to model complex attribute interactions to obtain good classification accuracy on practical problems. In this article, we propose to ...
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    Fast perceptron decision tree learning from evolving data streams 
    Bifet, Albert; Holmes, Geoffrey; Pfahringer, Bernhard; Frank, Eibe (Springer Berlin, 2010)
    Mining of data streams must balance three evaluation dimensions: accuracy, time and memory. Excellent accuracy on data streams has been obtained with Naive Bayes Hoeffding Trees—Hoeffding Trees with naive Bayes models at ...

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