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saattrupdan / doubt

Bringing back uncertainty to machine learning.
MIT License
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Conformal Quantile Regression #16

Open saattrupdan opened 3 years ago

saattrupdan commented 3 years ago

Conformal Quantile Regression was introduced in Romano, Patterson & Candès and is a variant of quantile regression which calibrates the prediction intervals, yielding narrower intervals, while preserving theoretical coverage guarantees.

This could potentially be built into QuantileLinearRegression via a conformal argument.

valeman commented 2 years ago

Dan, you might be interested in this link

https://github.com/valeman/awesome-conformal-prediction

leandroohf commented 1 year ago

Not sure if It is the right place for this message.

Since you mentioned Future work, you want to add support for neural networks. I would like to recommend looking into this paper: High-Quality Prediction Interval.

I started this notebook (WIP): https://github.com/leandroohf/machine_learning_algorithms/blob/master/dev/intro_to_prediction_interval.ipynb

and while doing my research, I discovered your packet doubt and decided to try.