awesome-shapley-value
shapley
| awesome-shapley-value | shapley | |
|---|---|---|
| 1 | 7 | |
| 133 | 211 | |
| 4.5% | - | |
| 3.2 | 2.7 | |
| almost 2 years ago | 10 months ago | |
| Python | ||
| Apache License 2.0 | MIT License |
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.
awesome-shapley-value
shapley
-
AstraZeneca Researchers Explain the Concept and Applications of the Shapley Value in Machine Learning
Code for https://arxiv.org/abs/2202.05594 found: https://github.com/benedekrozemberczki/shapley
- Calculating and approximating the Shapley value in voting games
- Show HN: Pruning Machine Learning Models with the Shapley Value
- Show HN: Shapley: Explaining Machine Learning Ensembles
- Shapley - a Python library for solving weighted voting games.
- Show HN: Shapley – a Python library for scoring ML models in an ensemble
What are some alternatives?
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.
DALEX - moDel Agnostic Language for Exploration and eXplanation
AIX360 - Interpretability and explainability of data and machine learning models
autogluon - Fast and Accurate ML in 3 Lines of Code
shap - A game theoretic approach to explain the output of any machine learning model. [Moved to: https://github.com/shap/shap]
sagemaker-explaining-credit-decisions - Amazon SageMaker Solution for explaining credit decisions.
DiCE - Generate Diverse Counterfactual Explanations for any machine learning model.
interpret - Fit interpretable models. Explain blackbox machine learning.
csle - A research platform to develop automated security policies using quantitative methods, e.g., optimal control, computational game theory, reinforcement learning, optimization, evolutionary methods, and causal inference.