Bringing back uncertainty to machine learning
Project description
Doubt
Bringing back uncertainty to machine learning.
A Python package to include prediction intervals in the predictions of machine learning models, to quantify their uncertainty.
Features
- Bootstrap wrapper for all Scikit-learn and PyTorch models
- Can also be used to calculate usual bootstrapped statistics of a dataset
- (Linear) Quantile Regression
- Quantile Regression Forests
- Quantile Neural Networks
- A uniform dataset API, with 24 regression datasets and counting
Quick Start
TODO
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