TalkToModel
TalkToModel gives anyone with the powers of XAI through natural language conversations 💬! (by dylan-slack)
DiCE
Generate Diverse Counterfactual Explanations for any machine learning model. (by interpretml)
TalkToModel | DiCE | |
---|---|---|
1 | 2 | |
102 | 1,270 | |
- | 0.9% | |
2.9 | 8.2 | |
9 months ago | 15 days ago | |
Python | Python | |
MIT License | MIT License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
TalkToModel
Posts with mentions or reviews of TalkToModel.
We have used some of these posts to build our list of alternatives
and similar projects.
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[R] TalkToModel: Understanding Machine Learning Models With Open Ended Dialogues
Code: https://github.com/dylan-slack/TalkToModel
DiCE
Posts with mentions or reviews of DiCE.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-01-31.
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[D] Have researchers given up on traditional machine learning methods?
- all domains requiring high interpretability absolutely ignore deep learning at all, and put all their research into traditional ML; see e.g. counterfactual examples, important interpretability methods in finance, or rule-based learning, important in medical or law applications
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[R] The Shapley Value in Machine Learning
Counter-factual and recourse-based explanations are alternative approach to model explanations. I used to work in a large financial institution, and we were researching whether counter-factual explanation methods would lead to better reason codes for adverse action notices.
What are some alternatives?
When comparing TalkToModel and DiCE you can also consider the following projects:
xi-method - Xi method
OmniXAI - OmniXAI: A Library for eXplainable AI