MOA is an open source framework for Big Data stream mining. It includes a collection of machine learning algorithms (classification, regression, clustering, outlier detection, concept drift detection and recommender systems) and tools for evaluation.
These modifications allow StreamKM to produce a clustering at any moment during the data stream, inline with the description given in M. R. Ackermann, M. Märtens, C. Raupach, K. Swierkot, C. Lammersen, and C. Sohler, “StreamKM++: A Clustering Algorithm for Data Streams,” ACM J. Exp. Algorithmics, vol. 17, no. 2, p. 30, Jul. 2012.
These modifications allow StreamKM to produce a clustering at any moment during the data stream, inline with the description given in M. R. Ackermann, M. Märtens, C. Raupach, K. Swierkot, C. Lammersen, and C. Sohler, “StreamKM++: A Clustering Algorithm for Data Streams,” ACM J. Exp. Algorithmics, vol. 17, no. 2, p. 30, Jul. 2012.
They also address Issue #70 and Issue #97.
Full development details are available here: https://github.com/richard-moulton/StreamKM