fseval

fseval: A Benchmarking Framework for Feature Selection and Feature Ranking Algorithms - Published in JOSS (2022)

https://github.com/dunnkers/fseval

Science Score: 98.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
    Found CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
    Found 7 DOI reference(s) in README and JOSS metadata
  • Academic publication links
    Links to: joss.theoj.org, zenodo.org
  • Committers with academic emails
  • Institutional organization owner
  • JOSS paper metadata
    Published in Journal of Open Source Software

Keywords

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

Keywords from Contributors

mesh

Scientific Fields

Mathematics Computer Science - 84% confidence
Last synced: 4 months ago · JSON representation ·

Repository

Benchmarking framework for Feature Selection and Feature Ranking algorithms 🚀

Basic Info
  • Host: GitHub
  • Owner: dunnkers
  • License: mit
  • Language: Python
  • Default Branch: master
  • Homepage: https://dunnkers.com/fseval
  • Size: 23.6 MB
Statistics
  • Stars: 19
  • Watchers: 2
  • Forks: 6
  • Open Issues: 0
  • Releases: 16
Topics
automl benchmarking benchmarking-framework benchmarks feature-rankers feature-ranking feature-selection hydra machine-learning python scikit-learn wandb
Created over 5 years ago · Last pushed over 2 years ago
Metadata Files
Readme Contributing License Code of conduct Citation

README.md

fseval

build status pypi badge Black Downloads PyPI - Python Version codecov Language grade: Python PyPI - License DOI Open in Remote - Containers DOI

Benchmarking framework for Feature Selection and Feature Ranking algorithms 🚀

Demo

Open In Colab

Install

  1. Installation through PyPi ⭐️ 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

See the documentation.

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.

2023 — Jeroen Overschie

Owner

  • Name: Jeroen Overschie
  • Login: dunnkers
  • Kind: user
  • Location: Amsterdam
  • Company: @Xebia @GoDataDriven

Machine Learning Engineer @ Xebia. Obtained a MSc Data Science and Systems Complexity at the University of Groningen.

JOSS Publication

fseval: A Benchmarking Framework for Feature Selection and Feature Ranking Algorithms
Published
November 23, 2022
Volume 7, Issue 79, Page 4611
Authors
Jeroen G. S. Overschie ORCID
Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence, University of Groningen, P.O. Box 407, 9700 AK Groningen, The Netherlands
Ahmad Alsahaf ORCID
Department of Biomedical Sciences of Cells and Systems, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands
George Azzopardi ORCID
Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence, University of Groningen, P.O. Box 407, 9700 AK Groningen, The Netherlands
Editor
Patrick Diehl ORCID
Tags
feature ranking feature selection benchmarking machine learning open-source software python

Citation (CITATION.cff)

cff-version: 1.2.0
message: "If you use fseval, please cite it as below."
authors:
- family-names: "Overschie"
  given-names: "Jeroen Gerard Sebastiaan"
  orcid: "https://orcid.org/0000-0003-3304-3800"
- family-names: "Alsahaf"
  given-names: "Ahmad"
  orcid: "https://orcid.org/0000-0002-0770-1390"
- family-names: "Azzopardi"
  given-names: "George"
  orcid: "https://orcid.org/0000-0001-6552-2596"
title: "fseval"
version: 3.1.0
doi: 10.21105/joss.04611
date-released: 2022-11-23
url: "https://joss.theoj.org/papers/10.21105/joss.04611"
preferred-citation:
  type: article
  authors:
  - family-names: "Overschie"
    given-names: "Jeroen Gerard Sebastiaan"
    orcid: "https://orcid.org/0000-0003-3304-3800"
  - family-names: "Alsahaf"
    given-names: "Ahmad"
    orcid: "https://orcid.org/0000-0002-0770-1390"
  - family-names: "Azzopardi"
    given-names: "George"
    orcid: "https://orcid.org/0000-0001-6552-2596"
  doi: "10.21105/joss.04611"
  journal: "Journal of Open Source Software"
  month: 11
  start: 1
  end: 5
  title: "fseval: A Benchmarking Framework for Feature Selection and Feature Ranking Algorithms"
  volume: 7
  number: 79
  publisher: "The Open Journal"
  pages: 4611
  year: 2022

GitHub Events

Total
  • Watch event: 1
Last Year
  • Watch event: 1

Committers

Last synced: 5 months ago

All Time
  • Total Commits: 409
  • Total Committers: 4
  • Avg Commits per committer: 102.25
  • Development Distribution Score (DDS): 0.037
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Jeroen Overschie j****e@g****m 394
dependabot[bot] 4****] 11
George Azzopardi g****o 2
AJ a****f@g****m 2

Issues and Pull Requests

Last synced: 4 months ago

All Time
  • Total issues: 55
  • Total pull requests: 38
  • Average time to close issues: about 1 month
  • Average time to close pull requests: 9 days
  • Total issue authors: 1
  • Total pull request authors: 7
  • Average comments per issue: 0.36
  • Average comments per pull request: 0.97
  • Merged pull requests: 32
  • Bot issues: 0
  • Bot pull requests: 16
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • dunnkers (55)
Pull Request Authors
  • dunnkers (18)
  • dependabot[bot] (15)
  • lgtm-com[bot] (1)
  • geazzo (1)
  • xuanxu (1)
  • amjams (1)
  • danielskatz (1)
Top Labels
Issue Labels
enhancement (12) bug (5) documentation (2) mustfix (1) question (1)
Pull Request Labels
dependencies (15) javascript (9)

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 30 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 1
  • Total versions: 12
  • Total maintainers: 1
pypi.org: fseval

Benchmarking framework for Feature Selection and Feature Ranking algorithms 🚀

  • Versions: 12
  • Dependent Packages: 0
  • Dependent Repositories: 1
  • Downloads: 30 Last month
Rankings
Dependent packages count: 7.3%
Forks count: 13.3%
Stargazers count: 15.2%
Average: 17.2%
Dependent repos count: 22.1%
Downloads: 27.9%
Maintainers (1)
Last synced: 4 months ago

Dependencies

website/package.json npm
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website/yarn.lock npm
  • 1042 dependencies
requirements.txt pypi
  • Boruta >=0.3
  • PyYAML >=6
  • SQLAlchemy >=1
  • dataclasses >=0.6
  • humanfriendly >=9
  • hydra-colorlog >=1.1
  • hydra-core >=1.1
  • l2x-synthetic >=2
  • numpy >=1.19
  • openml >=0.12
  • overrides >=6
  • pandas >=1
  • pytest-dependency *
  • scikit-learn >=0.24
  • scipy >=1.5
  • shortuuid >=1.0
  • skfeature-chappers >=1.0
  • skrebate >=0.62
  • types-PyYAML >=6
  • types-dataclasses >=0.6
  • wandb >=0.12
  • xgboost >=1
setup.py pypi
  • SQLAlchemy >=1
  • humanfriendly >=9
  • hydra-colorlog >=1.1.0
  • hydra-core >=1.1.0
  • numpy >=1.19
  • overrides >=6
  • pandas >=1.1
  • scikit-learn >=0.24
  • shortuuid >=1.0
.github/workflows/python-app.yml actions
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  • actions/setup-python v2 composite
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.github/workflows/python-publish.yml actions
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.devcontainer/Dockerfile docker
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.devcontainer/requirements.txt pypi
  • black * development
  • mypy ==0.982 development
  • pytest * development
  • pytest-cov * development
examples/comparing-feature-selectors/requirements.txt pypi
  • Boruta >=0.3
  • fseval *
  • skrebate >=0.62
  • xgboost >=1