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2009

Generalized density clustering

Rinaldo, Alessandro, Wasserman, Larry

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We study generalized density-based clustering in which sharply defined clusters such as clusters on lower-dimensional manifolds are allowed.

We show that accurate clustering is possible even in high dimensions.
We propose two data-based methods for choosing the bandwidth and we study the stability properties of density clusters.
We show that a simple graph-based algorithm successfully approximates the high density clusters.

Generalized density clustering · Around

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Federer, H
1969
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Hartigan, J
1975
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Devroye, L
1980
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Nolan, D
1987
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Mueller, D
1991
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Evans, L
1992
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Korostelev, A
1993
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Polonik, W
1995
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van der Vaart, A
1996
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Cuevas, A
1997
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Devroye, L
1997
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Tsybakov, A
1997
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Mammen, E
1999
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Mattila, P
1999
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