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A new nonsmooth optimization algorithm for minimum sum-of-squares clustering problems
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DOI：10.1016/j.ejor.2004.06.014.png)
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The minimum sum-of-squares clustering problem is formulated as a problem of nonsmooth, nonconvex optimization, and an algorithm for solving the former problem based on nonsmooth optimization techniques is developed. The issue of applying this algorithm to large data sets is discussed. Results of numerical experiments have been presented which demonstrate the effectiveness of the proposed algorithm. (c) 2004 Elsevier B.V. All rights reserved.
Keyword:
nonsmooth optimization
cluster analysis
minimum sum-of-squares clustering
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6
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2.2W
被引数:
6.4W
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