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fabsig / KTBoost

A Python package which implements several boosting algorithms with different combinations of base learners, optimization algorithms, and loss functions.

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Tobit with yl and yu varied by observations

kota7 opened this issue · comments

commented

Thanks for this repo!
I wonder if it is possible to extend the BoostingRegressor to work with the data where censoring points yl, yu are varied by observations.

commented

Thank you for using KTBoost!

Yes, this is possible. You basically have to add the option to use arrays instead of numbers for yl and yu in the TobitLossFunction. I currently don't have time to work on this. Contributions are welcome.