Probabilistic PCA and Factor Analysis

Version 1.0.0.0 (5,13 ko) par Mo Chen
EM algorithm for fitting PCA and FA model. This is probabilistic treatment of dimensional reduction.
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Mise à jour 13 mars 2016

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This package provides several functions that mainly use EM algorithm to fit probabilistic PCA and Factor analysis models.
PPCA is probabilistic counterpart of PCA model. PPCA has the advantage that it can be further extended to more advanced model, such as mixture of PPCA, Bayeisan PPCA or model dealing with missing data, etc. However, this package mainly served a research and teaching purpose for people to understand the model. The code is succinct so that it is easy to read and learn.
This package is now a part of the PRML toolbox (http://cn.mathworks.com/help/stats/ppca.html).

Citation pour cette source

Mo Chen (2024). Probabilistic PCA and Factor Analysis (https://www.mathworks.com/matlabcentral/fileexchange/55883-probabilistic-pca-and-factor-analysis), MATLAB Central File Exchange. Récupéré le .

Compatibilité avec les versions de MATLAB
Créé avec R2016a
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En savoir plus sur Dimensionality Reduction and Feature Extraction dans Help Center et MATLAB Answers
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Inspiré par : Pattern Recognition and Machine Learning Toolbox

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1.0.0.0

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