This function fist a probabilistic linear regression model with variational Bayesian inference. For the ordinary regularized linear regression, user has to manually assign the regularization parameter. However, Variational Bayesian method can do model selection automatically, that is it can automatically determine proper parameter from the data.
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 (2021). Variational Bayesian Linear Regression (https://www.mathworks.com/matlabcentral/fileexchange/55947-variational-bayesian-linear-regression), MATLAB Central File Exchange. Retrieved .
Inspired by: Pattern Recognition and Machine Learning Toolbox, Probabilistic Linear Regression
Inspired: Variational Bayesian Relevance Vector Machine for Sparse Coding
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Hi, thank you for your code , it's very useful. But I have some doubt , could you give me a favor? I want to know how to get the lower bound (energy(iter) = KLalpha+KLbeta+KLw) in code 'linRegVb.m'.
Thanks a lot for the help, very useful code!!!