Intrinsic Dimensionality Estimation of Submanifolds in Rd

Hein, M; Audibert, J-Y

doi:10.1145/1102351.1102388

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Intrinsic Dimensionality Estimation of Submanifolds in Rd

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Hein, M
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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https://dl.acm.org/citation.cfm?doid=1102351.1102388
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Zitation

Hein, M., & Audibert, J.-Y. (2005). Intrinsic Dimensionality Estimation of Submanifolds in Rd. In S. Dzeroski, L. de Raedt, & S. Wrobel (Eds.), ICML '05: 22nd international conference on Machine learning (pp. 289-296). New York, NY, USA: ACM Press.

Zitierlink: https://hdl.handle.net/11858/00-001M-0000-0013-D6DD-4

Zusammenfassung

We present a new method to estimate the intrinsic dimensionality of a submanifold M in Euclidean space from random samples. The method is based on the
convergence rates of a certain U-statistic on the manifold. We solve at least partially the question of the choice of the scale of the data.
Moreover the proposed method is easy to implement, can handle large data sets and performs very well even for small sample sizes. We compare the
proposed method to two standard estimators on several artificial as well as real data sets.