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).
Mo Chen (2023). Probabilistic Linear Regression (https://www.mathworks.com/matlabcentral/fileexchange/55832-probabilistic-linear-regression), MATLAB Central File Exchange. Retrieved .
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Inspired by: Pattern Recognition and Machine Learning Toolbox
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added model selection methods