Abstract:
In this talk, I will present recent advances in data stream mining, discussing their implementations in MOA. MOA is a software environment for running experiments for online learning from evolving data streams. It is designed to deal with the challenging problems of scaling up the implementation of state of the art algorithms to real world dataset sizes and of making algorithms comparable in benchmark
streaming settings. It contains a collection of algorithms for classification, clustering and pattern mining as well as tools for evaluation. MOA is based on the experience of WEKA, the Waikato Environment for Knowledge Analysis.

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