https://github.com/sply88/vcboost

Experimental tree boosted varying coefficient model
https://github.com/sply88/vcboost

gradient-boosting interpretable-machine-learning varying-coefficient-model

Last synced: 12 months ago
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Experimental tree boosted varying coefficient model

• Host: GitHub
• URL: https://github.com/sply88/vcboost
• Owner: sply88
• License: mit
• Created: 2021-01-20T06:48:59.000Z (about 5 years ago)
• Default Branch: master
• Last Pushed: 2021-10-20T14:07:37.000Z (over 4 years ago)
• Last Synced: 2025-01-08T01:48:33.106Z (about 1 year ago)
• Topics: gradient-boosting, interpretable-machine-learning, varying-coefficient-model
• Language: Python
• Homepage:
• Size: 818 KB
• Stars: 2
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# vcboost

Experimenting with estimation of varying coefficient models by gradient boosting.

The experimental implementation adapts the generic gradient boosting algorithm described in (Friedman 2001) and

can be found in [vcboost/boost.py](vcboost/boost.py).

The whole idea is mainly based on (Zhou 2019).

[sklearn decision trees](https://scikit-learn.org/stable/modules/generated/sklearn.tree.DecisionTreeRegressor.html) are used as base learners.

The [examples](examples) folder contains a few short notebooks.

- The [simple_interaction notebook](examples/simple_interaction.ipynb) illustrates the most basic case.

- In the [robust_loss notebook](examples/robust_loss.ipynb) the two currently available loss functions are compared

for the simple interaction example with added outliers.

- The [special_cases notebook](examples/special_cases.ipynb) shows how the algorithm relates to its special cases

*gradient boosting* and *ordinary least squares*.

- In the [wang_hastie notebook](examples/wang_hastie.ipynb) the model is applied to an example problem from the literature

## Background

Some details on the method are described in [background.pdf](background/background.pdf).

## References

***********

- Hastie, T., & Tibshirani, R. (1993). Varying‐coefficient models. Journal of the Royal Statistical Society: Series B (Methodological), 55(4), 757-779.

- Friedman, J. H. (2001). Greedy function approximation: a gradient boosting machine. Annals of statistics, 1189-1232.

- Zhou, Y., & Hooker, G. (2019). Tree boosted varying coefficient models. arXiv preprint arXiv:1904.01058