Intrinsic dimensionality estimation techniques

Implementation of some state-of-art intrinsic dimensionality estimators.
Updated 24 May 2013

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Data analysis is a fundamental step to face real Machine-Learning problems, various well-known ML techniques, such as those related to clustering or dimensionality reduction, require the intrinsic dimensionality (id) of the dataset as a parameter.

To the aim of automate the estimation of the id, in literature various techniques has been described, this small toolbox contains the implementation of some state-of-art of them, that is: MLE, MiND_ML, MiND_KL, DANCo, DANCoFit.

For an R implementation see:

Cite As

Gabriele Lombardi (2024). Intrinsic dimensionality estimation techniques (, MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2011b
Compatible with any release
Platform Compatibility
Windows macOS Linux

Inspired: Rand

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Version Published Release Notes

Added a reference to an R implementation in the description.