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@tqchen tqchen released this 15 Jan 00:00
· 5148 commits to master since this release
0.47
0dc68b1

This is last version release of 0.4 series, with many changes in the language bindings.

This is also a checkpoint before we switch to xgboost-brick #736

Changes

  • Changes in R library
    • fixed possible problem of poisson regression.
    • switched from 0 to NA for missing values.
    • exposed access to additional model parameters.
  • Changes in Python library
    • throws exception instead of crash terminal when a parameter error happens.
    • has importance plot and tree plot functions.
    • accepts different learning rates for each boosting round.
    • allows model training continuation from previously saved model.
    • allows early stopping in CV.
    • allows feval to return a list of tuples.
    • allows eval_metric to handle additional format.
    • improved compatibility in sklearn module.
    • additional parameters added for sklearn wrapper.
    • added pip installation functionality.
    • supports more Pandas DataFrame dtypes.
    • added best_ntree_limit attribute, in addition to best_score and best_iteration.
  • Java api is ready for use
  • Added more test cases and continuous integration to make each build more robust.
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