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Thresholds for XGBoost trees are forced to be float32 now (#168).
Fixed support for newer versions of XGBoost, in which the default value for the base_score parameter became None (#182).
Models can now be transpiled into the Dart language. Kudos to @MattConflitti for this great addition 🎉
Support for following models has been introduced:
Models from the statsmodels package are now supported. The list of added models includes: GLS, GLSAR, OLS, ProcessMLE, QuantReg and WLS.
Models from the lightning package: AdaGradRegressor/AdaGradClassifier, CDRegressor/CDClassifier, FistaRegressor/FistaClassifier, SAGARegressor/SAGAClassifier, SAGRegressor/SAGClassifier, SDCARegressor/SDCAClassifier, SGDClassifier, LinearSVR/LinearSVC and KernelSVC.
RANSACRegressor from the scikit-learn package.
The name of the scoring function can now be changed via a parameter. Thanks @mrshu 💪
The SubroutineExpr expression has been removed from AST. The logic of how to split the generated code into subroutines is now focused in interpreters and was completely removed from assemblers.