* Set output margin to True for custom objective in Python and R. * Add a demo for writing multi-class custom objective function. * Run tests on selected demos.
XGBoost Python Feature Walkthrough
- Basic walkthrough of wrappers
- Customize loss function, and evaluation metric
- Re-implement RMSLE as customized metric and objective
- Re-Implement
multi:softmaxobjective as customized objective - Boosting from existing prediction
- Predicting using first n trees
- Generalized Linear Model
- Cross validation
- Predicting leaf indices
- Sklearn Wrapper
- Sklearn Parallel
- Sklearn access evals result
- Access evals result
- External Memory