* Add a new API function for predicting on `DMatrix`. This function aligns with rest of the `XGBoosterPredictFrom*` functions on semantic of function arguments. * Purge `ntree_limit` from libxgboost, use iteration instead. * [dask] Use `inplace_predict` by default for dask sklearn models. * [dask] Run prediction shape inference on worker instead of client. The breaking change is in the Python sklearn `apply` function, I made it to be consistent with other prediction functions where `best_iteration` is used by default.
This folder contains testcases for xgboost.