Estimating the intrinsic dimension of data with a fractal-based method

Camastra, F. and Vinciarelli, A. (2002) Estimating the intrinsic dimension of data with a fractal-based method. IEEE Transactions on Pattern Analysis and Machine Intelligence, 24(10), pp. 1404-1407. (doi:10.1109/TPAMI.2002.1039212)

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Publisher's URL: http://dx.doi.org/10.1109/TPAMI.2002.1039212

Abstract

In this paper, the problem of estimating the intrinsic dimension of a data set is investigated. A fractal-based approach using the Grassberger-Procaccia algorithm is proposed. Since the Grassberger-Procaccia algorithm (1983) performs badly on sets of high dimensionality, an empirical procedure that improves the original algorithm has been developed. The procedure has been tested on data sets of known dimensionality and on time series of Santa Fe competition.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Vinciarelli, Professor Alessandro
Authors: Camastra, F., and Vinciarelli, A.
College/School:College of Science and Engineering > School of Computing Science
Journal Name:IEEE Transactions on Pattern Analysis and Machine Intelligence
ISSN:0162-8828

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