ARTICLE vincia02-art/IDIAP Estimating the Intrinsic Dimension of Data with a Fractal-Based Method Camastra, Francesco Vinciarelli, Alessandro EXTERNAL http://publications.idiap.ch/attachments/reports/2002/rr02-02.pdf PUBLIC http://publications.idiap.ch/index.php/publications/showcite/vincia02 Related documents IEEE Transactions on Pattern Analysis and Machine Intelligence 24 10 1404-1407 2002 IDIAP-RR 02-02 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 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. REPORT vincia02/IDIAP Estimating the Intrinsic Dimension of Data with a Fractal-Based Method Camastra, Francesco Vinciarelli, Alessandro EXTERNAL http://publications.idiap.ch/attachments/reports/2002/rr02-02.pdf PUBLIC Idiap-RR-02-2002 2002 IDIAP 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 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.