Intrinsic dimensionality estimation techniques

版本 1.1.0.0 (229.5 KB) 作者: Gabriele Lombardi
Implementation of some state-of-art intrinsic dimensionality estimators.
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更新时间 2013/5/24

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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:
http://www.maths.lth.se/matematiklth/personal/johnsson/dimest/

引用格式

Gabriele Lombardi (2024). Intrinsic dimensionality estimation techniques (https://www.mathworks.com/matlabcentral/fileexchange/40112-intrinsic-dimensionality-estimation-techniques), MATLAB Central File Exchange. 检索来源 .

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在 Help Center 和 MATLAB Answers 中查找有关 Dimensionality Reduction and Feature Extraction 的更多信息
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启发作品: Rand Sphere.zip

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idEstimation/

idEstimation/private/

idEstimation/html/

版本 已发布 发行说明
1.1.0.0

Added a reference to an R implementation in the description.
1.0.0.0