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The Top 23 Interpretability Explainability Open Source Projects

Open source projects categorized as Interpretability Explainability
Categories > Explainability
Categories > Machine Learning > Interpretability
Shap ⭐ 21,595
A game theoretic approach to explain the output of any machine learning model.
dependent packages 373total releases 100most recent commit 4 days agopypi shap} Downloads
Awesome Production Machine Learning ⭐ 15,804
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
most recent commit 24 days ago
Interpret ⭐ 5,992
Fit interpretable models. Explain blackbox machine learning.
dependent packages 28total releases 45most recent commit 3 days agopypi interpret} Downloads
Shapash ⭐ 2,547
🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models
dependent packages 2total releases 37most recent commit 3 months agopypi shapash} Downloads
Responsible Ai Toolbox ⭐ 1,187
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.
dependent packages 8total releases 6most recent commit 17 days agopypi raiutils} Downloads
Xai ⭐ 1,052
XAI - An eXplainability toolbox for machine learning
total releases 6most recent commit 2 years ago
Flashtorch ⭐ 712
Visualization toolkit for neural networks in PyTorch! Demo -->
total releases 12most recent commit 7 months ago
Transformer Mm Explainability ⭐ 490
[ICCV 2021- Oral] Official PyTorch implementation for Generic Attention-model Explainability for Interpreting Bi-Modal and Encoder-Decoder Transformers, a novel method to visualize any Transformer-based network. Including examples for DETR, VQA.
most recent commit a year ago
Neural Backed Decision Trees ⭐ 445
Making decision trees competitive with neural networks on CIFAR10, CIFAR100, TinyImagenet200, Imagenet
most recent commit 3 years ago
Explainx ⭐ 375
Explainable AI framework for data scientists. Explain & debug any blackbox machine learning model with a single line of code. We are looking for co-authors to take this project forward. Reach out @ [email protected]
total releases 56most recent commit 3 months ago
Adversarial Explainable Ai ⭐ 235
💡 Adversarial attacks on explanations and how to defend them
most recent commit 6 months ago
Sage ⭐ 205
For calculating global feature importance using Shapley values.
total releases 5most recent commit 5 months ago
Openxai ⭐ 178
OpenXAI : Towards a Transparent Evaluation of Model Explanations
most recent commit 6 months ago
Zennit ⭐ 151
Zennit is a high-level framework in Python using PyTorch for explaining/exploring neural networks using attribution methods like LRP.
dependent packages 2total releases 15most recent commit 7 months agopypi zennit} Downloads
Thermostat ⭐ 131
Collection of NLP model explanations and accompanying analysis tools
dependent packages 1total releases 5most recent commit 10 months agopypi thermostat-datasets} Downloads
Graphxai ⭐ 128
GraphXAI: Resource to support the development and evaluation of GNN explainers
most recent commit a year ago
Hierarchical Dnn Interpretations ⭐ 119
Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)
total releases 7most recent commit 3 years ago
Rrl ⭐ 82
The code of NeurIPS 2021 paper "Scalable Rule-Based Representation Learning for Interpretable Classification" and TPAMI paper "Learning Interpretable Rules for Scalable Data Representation and Classification"
most recent commit 3 months ago
Deep Explanation Penalization ⭐ 74
Code for using CDEP from the paper "Interpretations are useful: penalizing explanations to align neural networks with prior knowledge" https://arxiv.org/abs/1909.13584
most recent commit 3 years ago
Treeshap ⭐ 72
Compute SHAP values for your tree-based models using the TreeSHAP algorithm
total releases 1most recent commit 3 months ago
Talktomodel ⭐ 68
TalkToModel gives anyone with the powers of XAI through natural language conversations 💬!
most recent commit 9 months ago
Fat Forensics ⭐ 63
Modular Python Toolbox for Fairness, Accountability and Transparency Forensics
total releases 5most recent commit a year ago
Adaptive Wavelets ⭐ 60
Adaptive, interpretable wavelets across domains (NeurIPS 2021)
total releases 1most recent commit 2 years ago
The 6 Most Depended On Interpretability Explainability Open Source Projects
Shap ⭐ 21,595
A game theoretic approach to explain the output of any machine learning model.
dependent packages 373total releases 100latest release December 07, 2023most recent commit 4 days agopypi shap} Downloads
Interpret ⭐ 5,992
Fit interpretable models. Explain blackbox machine learning.
dependent packages 28total releases 45latest release August 26, 2023most recent commit 3 days agopypi interpret} Downloads
Shapash ⭐ 2,547
🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models
dependent packages 2total releases 37latest release December 08, 2023most recent commit 3 months agopypi shapash} Downloads
Thermostat ⭐ 131
Collection of NLP model explanations and accompanying analysis tools
dependent packages 1total releases 5latest release March 29, 2022most recent commit 10 months agopypi thermostat-datasets} Downloads
The 10 Latest Releases In Interpretability Explainability Open Source Projects
Shapash ⭐ 2,547
🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models
dependent packages 2total releases 37latest release December 08, 2023most recent commit 3 months agopypi shapash} Downloads
Shap ⭐ 21,595
A game theoretic approach to explain the output of any machine learning model.
dependent packages 373total releases 100latest release December 07, 2023most recent commit 4 days agopypi shap} Downloads
Treeshap ⭐ 72
Compute SHAP values for your tree-based models using the TreeSHAP algorithm
total releases 1latest release October 01, 2023most recent commit 3 months ago
Te2rules ⭐ 25
Python library to explain Tree Ensemble models (TE) like XGBoost, using a rule list.
total releases 16latest release August 31, 2023most recent commit 4 months ago
Interpret ⭐ 5,992
Fit interpretable models. Explain blackbox machine learning.
dependent packages 28total releases 45latest release August 26, 2023most recent commit 3 days agopypi interpret} Downloads
Tree_influence ⭐ 7
Influence Estimation for Gradient-Boosted Decision Trees
total releases 5latest release January 31, 2023most recent commit a year ago
Sage ⭐ 205
For calculating global feature importance using Shapley values.
total releases 5latest release January 07, 2023most recent commit 5 months ago
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