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S-means: similarity driven clustering and its application in gravitational-wave astronomy data mining

S-means: similarity driven clustering and its application in gravitational-wave astronomy data mining

This video was recorded at European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), Warsaw 2007. Clustering is to classify unlabeled data into groups. It has been wellresearched for decades in many disciplines. Clustering in massive amount of astronomical data generated by multi-sensor networks has become an emerging new challenge; assumptions in many existing clustering algorithms are often violated in these domains. For example, K means implicitly assumes that underlying distribution of data is Gaussian. Such an assumption is not necessarily observed in astronomical data. Another problem is the determination of K, which is hard to decide when prior knowledge is lacking. While there has been work done on discovering the proper... Show More
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