AIX360 VS awesome-shapley-value

Compare AIX360 vs awesome-shapley-value and see what are their differences.

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AIX360 awesome-shapley-value
2 1
1,533 133
2.0% 4.5%
8.2 3.2
2 months ago over 1 year ago
Python
Apache License 2.0 Apache License 2.0
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.

AIX360

Posts with mentions or reviews of AIX360. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-10-28.

awesome-shapley-value

Posts with mentions or reviews of awesome-shapley-value. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing AIX360 and awesome-shapley-value you can also consider the following projects:

AIF360 - A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.

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.

explainable-cnn - 📦 PyTorch based visualization package for generating layer-wise explanations for CNNs.

shapley - The official implementation of "The Shapley Value of Classifiers in Ensemble Games" (CIKM 2021).

cleverhans - An adversarial example library for constructing attacks, building defenses, and benchmarking both

shap - A game theoretic approach to explain the output of any machine learning model. [Moved to: https://github.com/shap/shap]

DiCE - Generate Diverse Counterfactual Explanations for any machine learning model.

DALEX - moDel Agnostic Language for Exploration and eXplanation

backpack - BackPACK - a backpropagation package built on top of PyTorch which efficiently computes quantities other than the gradient.

interpret - Fit interpretable models. Explain blackbox machine learning.

TorchDrift - Drift Detection for your PyTorch Models