semvec/pypi-packages huggingface dataset:
hypper 0.0.5
Hypergraph-based data mining tool for binary classification.
Keywords: hypergraphs machine-learning undersampling feature-selection classification

![](logo/logo1.png)

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Hypper is a data-mining Python library for binary classification. It uses hypergraph-based methods to explore datasets for the purpose of undersampling, feature selection and binary classification.

Hypper provides an easy-to-use interface familiar to well-recognized Scikit-Learn API. 

The primary goal of this library is to provide a tool for handling datasets consisting of mainly categorical features. Novel hypergraph-based methods proposed in the Hypper library were benchmarked against the alternative solutions and achieved satisfactory results. More details can be found in scientific papers presented in the section below.

## Installation
```bash
pip install hypper
```
Local installations
``` bash
pip install -e .['documentation'] # documentation
pip install -e .['develop'] # development (with testing)
pip install -e .['benchmarking'] # benchmarking scripts
pip install -e .['all'] # install everything
```

## Tutorials:
[![](https://colab.research.google.com/assets/colab-badge.svg)  1. Introduction to data mining with Hypper](https://colab.research.google.com/drive/1JntX8z3-e0qhCSjxpjYnPmfR2Iy09e15?usp=sharing)

## Testing
```bash
pytest
```
## Important links
* Source code - [https://github.com/hypper-team/hypper](https://github.com/hypper-team/hypper)
* Documentation - [https://hypper-team.github.io/hypper.html](https://hypper-team.github.io/hypper.html)

## Citation
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