explego

eXplego is a decision tree toolkit that provides developers with interactive guidance to help select an appropriate XAI-method for their particular use case.

https://github.com/norskregnesentral/explego

Science Score: 13.0%

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
  • DOI references
  • Academic publication links
  • Committers with academic emails
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (11.3%) to scientific vocabulary

Keywords

features interactive model prediction tool xai
Last synced: 6 months ago · JSON representation

Repository

eXplego is a decision tree toolkit that provides developers with interactive guidance to help select an appropriate XAI-method for their particular use case.

Basic Info
  • Host: GitHub
  • Owner: NorskRegnesentral
  • License: cc0-1.0
  • Default Branch: main
  • Homepage: http://explego.nr.no/
  • Size: 3.27 MB
Statistics
  • Stars: 5
  • Watchers: 1
  • Forks: 0
  • Open Issues: 1
  • Releases: 0
Topics
features interactive model prediction tool xai
Created over 3 years ago · Last pushed over 1 year ago
Metadata Files
Readme Changelog License Citation

README.md

eXplego

Explainability is key requisite for trustworthy AI, but selecting the right XAI-method to accompany your model development can be a challenging task. eXplego is a decision tree toolkit that provides developers with interactive guidance to help select an appropriate XAI-method for their particular use case.


[![Button Example]][Link]


To get to know the tool we recommend checking out the demonstration video below

English

YouTube

Norwegian

YouTube

More information about the tool, including a brief list with the reasoning for the positioning of every method in the tree, is provided in our short research paper:

Jullum, M., Sjødin, J., Prabhu, R., & Løland, A. (2023). eXplego: An interactive tool that helps you select appropriate XAI-methods for your explainability needs

which was presented as a demo at the 1st World Conference in Explainable AI (2023). To cite our tool, please use this citation.

We are very happy to receive feedback from our users on this tool. Please do so by opening an issue in this repo.

This is a collaborative project between Norwegian Computing Center and the Norwegian Labour and Welfare Administration (NAV), funded by BigInsight.

Explego v 1.0.3, last updated 2023-12-08. See changelog for details.

Owner

  • Name: Norsk Regnesentral (Norwegian Computing Center)
  • Login: NorskRegnesentral
  • Kind: organization
  • Location: Oslo, Norway

Norwegian Computing Center is a private foundation performing research in statistical modeling, machine learning and information/communication technology

GitHub Events

Total
  • Member event: 7
  • Push event: 1
Last Year
  • Member event: 7
  • Push event: 1

Committers

Last synced: about 1 year ago

All Time
  • Total Commits: 182
  • Total Committers: 5
  • Avg Commits per committer: 36.4
  • Development Distribution Score (DDS): 0.181
Past Year
  • Commits: 2
  • Committers: 2
  • Avg Commits per committer: 1.0
  • Development Distribution Score (DDS): 0.5
Top Committers
Name Email Commits
Martin Jullum j****m@n****o 149
Jacob Sjødin j****n@J****l 25
Anders Løland 3****d 5
Robindra Prabhu r****u@n****o 2
jacobInav 9****v 1
Committer Domains (Top 20 + Academic)
nav.no: 1 nr.no: 1

Issues and Pull Requests

Last synced: 12 months ago

All Time
  • Total issues: 0
  • Total pull requests: 7
  • Average time to close issues: N/A
  • Average time to close pull requests: 3 minutes
  • Total issue authors: 0
  • Total pull request authors: 2
  • Average comments per issue: 0
  • Average comments per pull request: 0.29
  • Merged pull requests: 5
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 2
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 1
  • Average comments per issue: 0
  • Average comments per pull request: 1.0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
Pull Request Authors
  • martinju (3)
  • andersloland (3)
Top Labels
Issue Labels
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