Statistics – Computation
Scientific paper
Dec 2005
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2005aspc..347..360m&link_type=abstract
Astronomical Data Analysis Software and Systems XIV ASP Conference Series, Vol. 347, Proceedings of the Conference held 24-27 Oc
Statistics
Computation
1
Scientific paper
Over the past decade, data mining has gained an important role in astronomical data analysis. Traditionally, such analysis is performed on data at a single location. However, one of the main motivational forces behind a virtual observatory is the distributed nature of both data and computational resources. Existing data-mining methods for distributed data are either communication-intensive or result in a loss of accuracy. In this paper, we introduce a general approach to supervised data mining that allows data to remain distributed, but still produces satisfactory results. We demonstrate by applying the approach to a number of astronomical datasets.
McConnell Sabine M.
Skillicorn D. B.
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