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Towards Effective Subspace Clustering with an Evolutionary Algorithm

, , , and . in: Proceedings of the IEEE Congress on Evolutionary Computation (CEC’03, (2003)

Abstract

This paper proposes a new evolutionary algorithm for subspace clustering in very large and high dimensional databases. The design includes task-specific coding and genetic operators, along with a non-random initialization procedure. Reported experimental results show the algorithm scales almost linearly with the size and dimensionality of the database as well as the dimensionality of the hidden clusters.

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Towards Effective Subspace Clustering with an Evolutionary Algorithm

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