Probabilistic PCA and Factor Analysis

Version 1.0.0.0 (5,13 KB) von Mo Chen
EM algorithm for fitting PCA and FA model. This is probabilistic treatment of dimensional reduction.
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Aktualisiert 13. Mär 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).

Zitieren als

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

Kompatibilität der MATLAB-Version
Erstellt mit R2016a
Kompatibel mit allen Versionen
Plattform-Kompatibilität
Windows macOS Linux
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Mehr zu Dimensionality Reduction and Feature Extraction finden Sie in Help Center und MATLAB Answers
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Inspiriert von: Pattern Recognition and Machine Learning Toolbox

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Version Veröffentlicht Versionshinweise
1.0.0.0

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