Instance-Based Uncertainty Estimation for Gradient-Boosted Regression Trees

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  • License: Apache Software License
  • Author: Jonathan Brophy
  • Requires: Python >=3.9
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IBUG: Instance-Based Uncertainty Estimation for Gradient-Boosted Regression Trees

PyPi version Python version Github License Build

ibug is a simple wrapper that extends any gradient-boosted regression trees (GBRT) model into a probabilistic estimator, and is compatible with all major GBRT frameworks including LightGBM, XGBoost, CatBoost, and SKLearn.

Install

pip install ibug

Experiment

Download a Dataset

  1. Follow the instructions in the readme for a dataset in data/.

Quantify Prediction Uncertainy with LightGBM + IBUG

python3 scripts/experiments/train.py --tree_type lgb
python3 scripts/experiments/predict.py --tree_type lgb

License

Apache License 2.0.

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  • License: Apache Software License
  • Author: Jonathan Brophy
  • Requires: Python >=3.9
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