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Author:
Ilia Azizi, Juraj Bodik, Jakob Heiss, Bin Yu
License:
MIT
Summary:
CLEAR: Calibrated Learning for Epistemic and Aleatoric Risk - Uncertainty quantification for regression
Latest version:
0.3.1
Required dependencies:
catboost
|
celer
|
joblib
|
lightgbm
|
matplotlib
|
matplotlib-inline
|
numpy
|
openml
|
pandas
|
plotly
|
pygam
|
pytest
|
quantile-forest
|
scikit-learn
|
scikit-lego
|
scipy
|
seaborn
|
setuptools
|
tcl
|
torch
|
tqdm
|
ucimlrepo
|
xgboost
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