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https://github.com/dunnkers/fseval

Benchmarking framework for Feature Selection and Feature Ranking algorithms 🚀
https://github.com/dunnkers/fseval

automl benchmarking benchmarking-framework benchmarks feature-rankers feature-ranking feature-selection hydra machine-learning python scikit-learn wandb

Last synced: 22 days ago
JSON representation

Benchmarking framework for Feature Selection and Feature Ranking algorithms 🚀

Host: GitHub
URL: https://github.com/dunnkers/fseval
Owner: dunnkers
License: mit
Created: 2020-06-21T23:46:25.000Z (over 4 years ago)
Default Branch: master
Last Pushed: 2023-04-12T09:57:56.000Z (over 1 year ago)
Last Synced: 2024-10-01T15:44:18.076Z (about 1 month ago)
Topics: automl, benchmarking, benchmarking-framework, benchmarks, feature-rankers, feature-ranking, feature-selection, hydra, machine-learning, python, scikit-learn, wandb
Language: Python
Homepage: https://dunnkers.com/fseval
Size: 23.6 MB
Stars: 18
Watchers: 3
Forks: 6
Open Issues: 0
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
- Citation: CITATION.cff

Awesome Lists containing this project

README

        # fseval

[![build status](https://github.com/dunnkers/fseval/actions/workflows/python-app.yml/badge.svg)](https://github.com/dunnkers/fseval/actions/workflows/python-app.yml)

[![pypi badge](https://img.shields.io/pypi/v/fseval.svg?maxAge=3600)](https://pypi.org/project/fseval/)

[![Black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)

[![Downloads](https://pepy.tech/badge/fseval/month)](https://pepy.tech/project/fseval) ![PyPI - Python Version](https://img.shields.io/pypi/pyversions/fseval)

[![codecov](https://codecov.io/gh/dunnkers/fseval/branch/master/graph/badge.svg?token=R5ZXH8UPCI)](https://codecov.io/gh/dunnkers/fseval)

[![Language grade: Python](https://img.shields.io/lgtm/grade/python/g/dunnkers/fseval.svg?logo=lgtm&logoWidth=18)](https://lgtm.com/projects/g/dunnkers/fseval/context:python) ![PyPI - License](https://img.shields.io/pypi/l/fseval)

[![DOI](https://zenodo.org/badge/274001213.svg)](https://zenodo.org/badge/latestdoi/274001213)

[![Open in Remote - Containers](https://img.shields.io/static/v1?label=Remote%20-%20Containers&message=Open&color=blue&logo=visualstudiocode)](https://vscode.dev/redirect?url=vscode://ms-vscode-remote.remote-containers/cloneInVolume?url=https://github.com/dunnkers/fseval)

[![DOI](https://joss.theoj.org/papers/10.21105/joss.04611/status.svg)](https://doi.org/10.21105/joss.04611)

Benchmarking framework for Feature Selection and Feature Ranking algorithms 🚀

## Demo

[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1Bsuxxuw0-mEsYRSnNbmvD_wNUAkOPiQa?usp=sharing)

## Install

1. Installation through [PyPi](https://pypi.org/project/fseval/)

    ^{_{⭐️ RECOMMENDED OPTION}}

    ```shell

    pip install fseval

    ```

2. Installation from source 

    ```shell

    git clone https://github.com/dunnkers/fseval.git

    cd fseval

    pip install -r requirements.txt

    pip install .

    ```

You can now import fseval `import fseval` in your Python code, or use the `fseval` command in your terminal. For an example, run `fseval --help`. For more information, see the documentation link below ⌄. 

## Documentation

[![docs preview](./website/static/img/docs-preview.png)](https://dunnkers.com/fseval)

See the [documentation](https://dunnkers.com/fseval).

## About

Built at the University of Groningen and published in **The Journal of Open Source Software** (JOSS):

- https://joss.theoj.org/papers/10.21105/joss.04611

Project has some early roots in another project, which is a feature selection algorithm called FeatBoost (see full citation below).

A. Alsahaf, N. Petkov, V. Shenoy, G. Azzopardi, "A framework for feature selection through boosting", Expert Systems with Applications,

Volume 187, 2022, 115895, ISSN 0957-4174, https://doi.org/10.1016/j.eswa.2021.115895.

    

The open source Python code of FeatBoost is available in https://github.com/amjams/FeatBoost.

   

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2023 — Jeroen Overschie