CiteSeerX - Document Details (Isaac Councill, Lee Giles): 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.