Science Score: 36.0%

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

  • CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
  • Academic publication links
  • Committers with academic emails
    2 of 10 committers (20.0%) from academic institutions
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (9.0%) to scientific vocabulary

Keywords

feature-selection scikit-learn
Last synced: 6 months ago · JSON representation

Repository

Basic Info
  • Host: GitHub
  • Owner: NoRaincheck
  • License: gpl-2.0
  • Language: Python
  • Default Branch: master
  • Size: 120 MB
Statistics
  • Stars: 33
  • Watchers: 4
  • Forks: 18
  • Open Issues: 3
  • Releases: 1
Topics
feature-selection scikit-learn
Created over 8 years ago · Last pushed about 1 year ago
Metadata Files
Readme Changelog License

README.md

scikit-feature is an open-source (GNU General Public License v2.0) feature selection repository in Python developed by Data Mining and Machine Learning Lab at Arizona State University.

It serves as a platform for facilitating feature selection application, research and comparative study. It is designed to share widely used feature selection algorithms developed in the feature selection research, and offer convenience for researchers and practitioners to perform empirical evaluation in developing new feature selection algorithms.

This is may or may not be a temporary fork of the original repository as development seems to have stalled and various modules have be depreciated due to updates to scikit-learn. I will see if should get reintegrated back into the original project if it ever gets revived again.

Forked project information

  • Project site - https://github.com/HeardACat/scikit-feature

Original scikit-feature project information

  • Project site - https://github.com/jundongl/scikit-feature
  • Documentation - http://featureselection.asu.edu/

Installation

From Sources

  • Unpack the source package somewhere
  • Run pip install -e . from the source distribution's top level folder

From pip

```sh pip install skfeature-chappers

```

Owner

  • Login: NoRaincheck
  • Kind: user
  • Location: Nowhere

I build stuff

GitHub Events

Total
  • Watch event: 1
  • Fork event: 2
Last Year
  • Watch event: 1
  • Fork event: 2

Committers

Last synced: 9 months ago

All Time
  • Total Commits: 146
  • Total Committers: 10
  • Avg Commits per committer: 14.6
  • Development Distribution Score (DDS): 0.582
Past Year
  • Commits: 13
  • Committers: 1
  • Avg Commits per committer: 13.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
jundongl j****l@a****u 61
Chapman Siu c****u@g****m 46
CS 2****3 14
HeardACat 2****t 13
vivian1993 v****3 3
bacalfa b****a@g****m 3
Guangyu Li g****3@c****u 3
Gary Marigliano g****3@g****m 1
tadej t****j 1
Daniel Novaes h****g@g****m 1
Committer Domains (Top 20 + Academic)

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 7
  • Total pull requests: 6
  • Average time to close issues: almost 5 years
  • Average time to close pull requests: 12 months
  • Total issue authors: 6
  • Total pull request authors: 4
  • Average comments per issue: 0.71
  • Average comments per pull request: 0.83
  • Merged pull requests: 5
  • Bot issues: 0
  • Bot pull requests: 0
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
Pull Request Authors
Top Labels
Issue Labels
Pull Request Labels

Dependencies

.github/workflows/main.yml actions
  • actions/checkout v2 composite
  • actions/setup-python v2 composite
  • codecov/codecov-action v1 composite
pyproject.toml pypi
setup.py pypi