Intrinsic dimensionality estimation techniques

Implementation of some state-of-art intrinsic dimensionality estimators.
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Mise à jour 24 mai 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:

Citation pour cette source

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

Compatibilité avec les versions de MATLAB
Créé avec R2011b
Compatible avec toutes les versions
Plateformes compatibles
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En savoir plus sur Dimensionality Reduction and Feature Extraction dans Help Center et MATLAB Answers

A inspiré : Rand

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Version Publié le Notes de version

Added a reference to an R implementation in the description.