Data dimensionality estimation methods: a survey |
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Authors: | Francesco |
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Affiliation: | INFM - DISI, University of Genova, Via Dodecaneso 35, Genova 16146, Italy |
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Abstract: | In this paper, data dimensionality estimation methods are reviewed. The estimation of the dimensionality of a data set is a classical problem of pattern recognition. There are some good reviews (Algorithms for Clustering Data, Prentice-Hall, Englewood Cliffs, NJ, 1988) in literature but they do not include more recent developments based on fractal techniques and neural autoassociators. The aim of this paper is to provide an up-to-date survey of the dimensionality estimation methods of a data set, paying special attention to the fractal-based methods. |
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Keywords: | Intrinsic dimensionality Topological dimension Fukunaga–Olsen's algorithm Fractal dimension Multidimensional scaling |
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