Abstract
Stellar data, only a few years ago, measured in the .1M of objects. Now, sets are routinely 1M. With the launch of ESA's Gaia in 2013, we expect 1000M stellar objects measured more precisely and with more measurements. Without question, astronomy is about Big Data and clustering is a very common task over astronomy domain. The expectation-maximization algorithm is among the top 10 data mining algorithms used in scientific and industrial applications, however, we observe that astronomical community does not make use of it as a clustering algorithm. In this work, we cluster ā¼ 1M stellar objects (simulated Galactic spectral data) via the traditional expectation-maximization algorithm for clustering (EM-T) and our extended EM-T algorithm that we call EMā and present the experimental results.
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