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xgboost/R-package/demo
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Jiaming Yuan d262503781 [R] Implement new save raw in R. (#7571)
2022-01-22 20:55:47 +08:00
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basic_walkthrough.R
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boost_from_prediction.R
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caret_wrapper.R
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create_sparse_matrix.R
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cross_validation.R
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custom_objective.R
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early_stopping.R
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generalized_linear_model.R
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gpu_accelerated.R
[CI] Improve R linter script (#5944)
2020-07-27 00:55:35 -07:00
interaction_constraints.R
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poisson_regression.R
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predict_first_ntree.R
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predict_leaf_indices.R
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README.md
Fix spelling in documents (#6948)
2021-05-11 20:44:36 +08:00
runall.R
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tweedie_regression.R
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README.md

XGBoost R Feature Walkthrough

  • Basic walkthrough of wrappers
  • Train a xgboost model from caret library
  • Customize loss function, and evaluation metric
  • Boosting from existing prediction
  • Predicting using first n trees
  • Generalized Linear Model
  • Cross validation
  • Create a sparse matrix from a dense one
  • Use GPU-accelerated tree building algorithms

Benchmarks

  • Starter script for Kaggle Higgs Boson

Notes

  • Contribution of examples, benchmarks is more than welcomed!
  • If you like to share how you use xgboost to solve your problem, send a pull request :)
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