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I guess when predicting, you can specify how many trees to be used. But currently, xgboost4j has not supported specifying the tree limit. I will make a PR for it.
Does xgboost4j-spark support to get the best model after early stop?
It seems it will get the model at that iteration which is best iteration + num_early_stopping_rounds, am i wrong?
how could i get the best model?
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