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Published in:
2008 | OriginalPaper | Chapter
Classifying Evolving Data Streams Using Dynamic Streaming Random Forests
Authors : Hanady Abdulsalam, David B. Skillicorn, Patrick Martin
Published in: Database and Expert Systems Applications
Publisher: Springer Berlin Heidelberg
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We consider the problem of data-stream classification, introducing a stream-classification algorithm,
Dynamic Streaming Random Forests
, that is able to handle evolving data streams using an entropy-based drift-detection technique. The algorithm automatically adjusts its parameters based on the data seen so far. Experimental results show that the algorithm handles multi-class problems for which the underlying class boundaries drift, without losing accuracy.