v0.13.0

EvoTrees v0.13.0

(Multi)Classification / softmax now supported on GPU through EvoClassifier(device = "gpu", ...)
No more export of grow_tree! and predict.
For prediction / inference, the recommended to approach is (m::EvoTree)(x).
The fitted model struct is now EvoTree / EvoTreeGPU. (previously was GBTree / GBTreeGPU).
fit_evotree can now return the tracking of the metrics throughout the iterations by using return_logger = true as kwarg. Example:

m, logger = fit_evotree(config; x_train, y_train, x_eval, y_eval, metric=:logloss, print_every_n=50, early_stopping_rounds=100, return_logger = true)

Diff since v0.12.5

Closed issues:

• Feature request: support EvoTreeClassifier(loss = Softmax()) on the GPU (#139)
• MLJModelInterface.fit does not accept tables? (#169)
• Plot loss curve history for train and eval data set (#178)
• GPU for classifiers (#185)
• GPU saved model not possible open without CUDA (#189)

Merged pull requests:

• Logger (#183) (@jeremiedb)
• Add ntree_limit for predict (#184) (@Moelf)
• massively reduce CPU allocation (#186) (@Moelf)
• Dev (#187) (@jeremiedb)
• Gpu upgrade (#188) (@jeremiedb)
• Dev (#190) (@jeremiedb)
• Add generic MLJ interface tests (#191) (@ablaom)