Intrinsic Dimension Estimation Using Packing Numbers

We propose a new algorithm to estimate the intrinsic dimension of data sets. The method is based on geometric properties of the data and requires neitherparametric assumptions on the data generating model nor input parameters to set. The method is compared to a similar, widelyused algorithmfrom the same family of geometric techniques. Experiments showthat our method is more robust in terms of the data generating distribution and more reliable in the presence of noise.