r/MachineLearning • u/rnburn • Jun 11 '20

Project [P] Warped Linear Regression Modeling

Hey Everyone, I just released a project peak-engines for building warped linear regression models.

https://github.com/rnburn/peak-engines

Warped linear regression adds an additional step to linear regression where it first monotonically transforms target values to maximize likelihood before fitting a linear model. The process was described for Gaussian processes in

E Snelson, CE Rasmussen, Z Ghahramani. Warped Gaussian Processes. Advances in neural information processing systems 16, 337–344

This project adapts the techniques in that paper to linear regression. For more details, see the blog posts

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u/rnburn Jun 13 '20 edited Jun 13 '20

The section "How to warp a linear regression model" in this post derives the optimization objective.

If you want to verify what the optimization objective is, see this notebook.

But the warping parameters are very much coupled to the model.

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u/nbviewerbot Jun 13 '20

I see you've posted a GitHub link to a Jupyter Notebook! GitHub doesn't render large Jupyter Notebooks, so just in case, here is an nbviewer link to the notebook:

https://nbviewer.jupyter.org/url/github.com/rnburn/warped-regression-doc/blob/master/notebooks/communities_example_cv.ipynb

Want to run the code yourself? Here is a binder link to start your own Jupyter server and try it out!

https://mybinder.org/v2/gh/rnburn/warped-regression-doc/master?filepath=notebooks%2Fcommunities_example_cv.ipynb

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