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UNIQUE v0.2.2
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<figure> | ||
<img src=./docs/source/_static/unique_logo_blue.png alt="UNIQUE Logo"> | ||
<img src="https://github.com/Novartis/UNIQUE/raw/main/docs/source/_static/unique_logo_blue.png" alt="UNIQUE Logo"> | ||
<figcaption align=center><u><b>UN</b></u>certa<u><b>I</b></u>nty <u><b>QU</b></u>antification b<u><b>E</b></u>nchmark: a Python library for benchmarking uncertainty estimation and quantification methods for Machine Learning models predictions.</figcaption> | ||
</figure> | ||
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[![Python](https://img.shields.io/pypi/pyversions/unique-uncertainty?label=Python)](https://pypi.org/project/unique-uncertainty/) | ||
[![version](https://img.shields.io/pypi/v/unique-uncertainty?color=green&label=PyPI)](https://pypi.org/project/unique-uncertainty/) | ||
[![PyPI downloads](https://img.shields.io/pypi/dm/unique-uncertainty?label=Downloads)](https://pypi.org/project/unique-uncertainty/) | ||
[![PyPI version](https://img.shields.io/pypi/v/unique-uncertainty?color=green&label=PyPI)](https://pypi.org/project/unique-uncertainty/) | ||
[![Conda version](https://img.shields.io/conda/vn/conda-forge/unique-uncertainty?color=green&label=conda-forge)](https://anaconda.org/conda-forge/unique-uncertainty) | ||
[![License](https://img.shields.io/badge/License-BSD_3--Clause-red)](https://opensource.org/licenses/BSD-3-Clause) | ||
[![chemRxiv](https://img.shields.io/badge/chemRxiv-10.26434%2Fchemrxiv--2024--fmbgk-yellow)](https://doi.org/10.26434/chemrxiv-2024-fmbgk) | ||
[![PyPI downloads](https://img.shields.io/pypi/dm/unique-uncertainty?color=yellowgreen&label=PyPI%20downloads)](https://pypi.org/project/unique-uncertainty/) | ||
[![Conda downloads](https://img.shields.io/conda/dn/conda-forge/unique-uncertainty?color=yellowgreen&label=conda%20downloads)](https://anaconda.org/conda-forge/unique-uncertainty) | ||
[![Docs](https://github.com/Novartis/UNIQUE/actions/workflows/docs.yml/badge.svg?branch=main)](https://opensource.nibr.com/UNIQUE/) | ||
[![Build](https://github.com/Novartis/UNIQUE/actions/workflows/build.yml/badge.svg?branch=main)](https://pypi.org/project/unique-uncertainty/) | ||
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`UNIQUE` is a model-agnostic tool, meaning that it does not depend on any specific ML model building platform or provides any ML model training functionality. It is lightweight, because it only requires the user to input their model's inputs and predictions. | ||
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<figure> | ||
<img src=./docs/source/_static/schema_high_level.png alt="UNIQUE High Level Schema"> | ||
<img src="https://github.com/Novartis/UNIQUE/raw/main/docs/source/_static/schema_high_level.png" alt="UNIQUE High Level Schema"> | ||
<figcaption align=center>High-level schema of <code>UNIQUE</code>'s components.</figcaption> | ||
</figure> | ||
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## Installation | ||
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[![Python](https://img.shields.io/pypi/pyversions/unique-uncertainty?label=Python)](https://pypi.org/project/unique-uncertainty/) | ||
[![version](https://img.shields.io/pypi/v/unique-uncertainty?color=green&label=PyPI)](https://pypi.org/project/unique-uncertainty/) | ||
[![PyPI downloads](https://img.shields.io/pypi/dm/unique-uncertainty?label=Downloads)](https://pypi.org/project/unique-uncertainty/) | ||
[![PyPI version](https://img.shields.io/pypi/v/unique-uncertainty?color=green&label=PyPI)](https://pypi.org/project/unique-uncertainty/) | ||
[![Conda version](https://img.shields.io/conda/vn/conda-forge/unique-uncertainty?color=green&label=conda-forge)](https://anaconda.org/conda-forge/unique-uncertainty) | ||
[![PyPI downloads](https://img.shields.io/pypi/dm/unique-uncertainty?color=yellowgreen&label=PyPI%20downloads)](https://pypi.org/project/unique-uncertainty/) | ||
[![Conda downloads](https://img.shields.io/conda/dn/conda-forge/unique-uncertainty?color=yellowgreen&label=conda%20downloads)](https://anaconda.org/conda-forge/unique-uncertainty) | ||
[![Build](https://github.com/Novartis/UNIQUE/actions/workflows/build.yml/badge.svg?branch=main)](https://pypi.org/project/unique-uncertainty/) | ||
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`UNIQUE` is currently compatible with Python 3.8 through 3.12.1. To install the latest release and use the package as is, run the following in a compatible environment of choice: | ||
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pip install unique-uncertainty | ||
``` | ||
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or: | ||
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```bash | ||
conda install -c conda-forge unique-uncertainty | ||
# mamba install -c conda-forge unique-uncertainty | ||
``` | ||
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Check out the [docs](https://opensource.nibr.com/UNIQUE/installation.html#installation) for more installation instructions. | ||
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## License | ||
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[![License](https://img.shields.io/badge/License-BSD_3--Clause-red)](https://opensource.org/licenses/BSD-3-Clause) | ||
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`UNIQUE` is licensed under the BSD 3-Clause License. See the [LICENSE](./LICENSE.md) file. | ||
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## Cite Us | ||
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[![chemRxiv](https://img.shields.io/badge/chemRxiv-10.26434%2Fchemrxiv--2024--fmbgk-yellow)](https://doi.org/10.26434/chemrxiv-2024-fmbgk) | ||
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If you find `UNIQUE` helpful for your work and/or research, please consider citing our work: | ||
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```bibtex | ||
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* **[Raquel Rodríguez-Pérez](mailto:[email protected]?subject=UNIQUE)** | ||
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![Novartis Logo](./docs/source/_static/novartis_logo.png) | ||
![Novartis Logo](https://github.com/Novartis/UNIQUE/raw/main/docs/source/_static/novartis_logo.png) |
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