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At the moment this is not in our priority list as it doesn't seems that users are keen to have this feature. I would be happy to follow if somebody decides to take this up. First of all we need a list of use cases to define when/how users may want to use this (possibly using the existing datasets).
We don't want to provide anything through bindings, there are already other libraries that do that pretty well; what put in there library has to go through some criteria that are loosely defined in CONTRIBUTING and DEVELOPERS.
I'm submitting a
Expected Behaviour:
smartcore
should provide an implementation for gradient boosting (XGBoost) for most popular regressions:forust-ml
gradient boosting libraryLet's try to find a low foot-print and feature-enabled solution to provide this great tool.
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