Probabilistic Linear Regression

Version 1.0.0.0 (4.26 KB) by Mo Chen
Probabilistic Linear Regression with automatic model selection
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Updated 13 Mar 2016

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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).

Cite As

Mo Chen (2024). Probabilistic Linear Regression (https://www.mathworks.com/matlabcentral/fileexchange/55832-probabilistic-linear-regression), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2016a
Compatible with any release
Platform Compatibility
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Version Published Release Notes
1.0.0.0

added model selection methods
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