Probabilistic Linear Regression
This package contains functions that fit a probabilistic linear regression model. For the ordinary regularized linear regression, user has to manually assign the regularization parameter. However, here we provide methods to automatically determine proper parameter from the data.
Two methods have been used to determine the regularization parameter: one uses the EM algorithm, the other uses the Mackay fix point update method. There are also demos and docs in this package.
This package is now a part of the PRML Toolbox (http://www.mathworks.com/matlabcentral/fileexchange/55826-pattern-recognition-and-machine-learning-toolbox).
Citation pour cette source
Mo Chen (2024). Probabilistic Linear Regression (https://www.mathworks.com/matlabcentral/fileexchange/55832-probabilistic-linear-regression), MATLAB Central File Exchange. Récupéré le .
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Inspiré par : Pattern Recognition and Machine Learning Toolbox
A inspiré : Bayesian Compressive Sensing (sparse coding) and Relevance Vector Machine, Variational Bayesian Linear Regression, Variational Bayesian Relevance Vector Machine for Sparse Coding
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linReg/
Version | Publié le | Notes de version | |
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1.0.0.0 |
added model selection methods
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