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Library for Multi-objective optimization in Gradient Boosted Trees

License: BSD 3-Clause "New" or "Revised" License

Python 100.00%
machine-learning machine-learning-algorithms multi-objective-optimization constrained-optimization gradient-boosted-trees

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moo-gbt's Issues

MOO for multi-class classification

Hi,
Dose the current package support constraints for multi-class classification? I believe the constraints affect the overall training by altering the leaf node values in the _update_terminal_region member function, which is implemented in each loss function class. But I see that only for LeastSquaresError and BinomialDeviance classes, the additional labels are being used to impose constraints. Is there any other place in the code where constraints are used to affect the multi-class loss, i.e. MultinomialDeviance ?

Thanks,
Deb

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