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Intrinsic dimension estimation of data: an approach based on Grassberger-Procaccia's algorithm
2000
In this paper the problem of estimating the intrinsic dimension of a data set is investigated. An approach based on the Grassberger-Procaccia's algorithm has been studied. Since this algorithm does not yield accurate measures in high-dimensional data sets, an empirical procedure has been developed. Grassberger-Procaccia's algorithm was tested on two different benchmarks and was compared to a TRN-based method.
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rr00-33.pdf
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openaccess
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216.71 KB
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