easy_explain
awesome-shapley-value
easy_explain | awesome-shapley-value | |
---|---|---|
1 | 1 | |
9 | 133 | |
- | 4.5% | |
6.5 | 3.2 | |
2 months ago | almost 2 years ago | |
Python | ||
MIT License | Apache License 2.0 |
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.
easy_explain
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Do you want an easy and quick way to explain your image models?
Find the package in Gh: https://github.com/stavrostheocharis/easy_explain
awesome-shapley-value
What are some alternatives?
tf-keras-vis - Neural network visualization toolkit for tf.keras
responsible-ai-toolbox - Responsible AI Toolbox is a suite of tools providing model and data exploration and assessment user interfaces and libraries that enable a better understanding of AI systems. These interfaces and libraries empower developers and stakeholders of AI systems to develop and monitor AI more responsibly, and take better data-driven actions.
AIX360 - Interpretability and explainability of data and machine learning models
shapley - The official implementation of "The Shapley Value of Classifiers in Ensemble Games" (CIKM 2021).
shap - A game theoretic approach to explain the output of any machine learning model. [Moved to: https://github.com/shap/shap]
DALEX - moDel Agnostic Language for Exploration and eXplanation
interpret - Fit interpretable models. Explain blackbox machine learning.