[PR #2663] Add SHAP, LIME, InterpretML under ML and DGL under DL #1979

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GiteaMirror · 2025-11-06T13:27:01-06:00

GiteaMirror commented

2025-11-06 13:27:01 -06:00

📋 Pull Request Information

Original PR: https://github.com/vinta/awesome-python/pull/2663
Author: @YADIDidiah24
Created: 3/17/2025
Status: 🔄 Open

Base: master ← Head: add-explainable-ai

📝 Commits (1)

9ad63f0 Add SHAP, LIME, InterpretML under ML and DGL under DL

📊 Changes

1 file changed (+4 additions, -2 deletions)

View changed files

📝 README.md (+4 -2)

📄 Description

What is this Python project?

This PR adds SHAP, LIME, and InterpretML under Machine Learning and DGL under Deep Learning.

SHAP (SHapley Additive exPlanations) provides game-theory-based feature explanations for ML models.
LIME (Local Interpretable Model-agnostic Explanations) explains predictions locally by analyzinginputs.
InterpretML is a framework for training interpretable models and explaining black-box systems.
DGL (Deep Graph Library) is a flexible framework designed for deep learning on graphs.

What's the difference between this Python project and similar ones?

Enumerate comparisons.

These libraries are widely used for Explainable AI (XAI) and interpretable machine learning, distinguishing them from general-purpose ML libraries.

DGL vs. Other DL Frameworks: DGL specializes in graph neural networks (GNNs), unlike PyTorch or TensorFlow, which focus on general deep learning.

Anyone who agrees with this pull request could submit an Approve review to it.

_{🔄 This issue represents a GitHub Pull Request. It cannot be merged through Gitea due to API limitations.}

## 📋 Pull Request Information **Original PR:** https://github.com/vinta/awesome-python/pull/2663 **Author:** [@YADIDidiah24](https://github.com/YADIDidiah24) **Created:** 3/17/2025 **Status:** 🔄 Open **Base:** `master` ← **Head:** `add-explainable-ai` --- ### 📝 Commits (1) - [`9ad63f0`](https://github.com/vinta/awesome-python/commit/9ad63f087d6f183121bc9faef12c5b3a190e69bf) Add SHAP, LIME, InterpretML under ML and DGL under DL ### 📊 Changes **1 file changed** (+4 additions, -2 deletions) <details> <summary>View changed files</summary> 📝 `README.md` (+4 -2) </details> ### 📄 Description ## What is this Python project? This PR adds SHAP, LIME, and InterpretML under Machine Learning and DGL under Deep Learning. 1. SHAP (SHapley Additive exPlanations) provides game-theory-based feature explanations for ML models. 2. LIME (Local Interpretable Model-agnostic Explanations) explains predictions locally by analyzinginputs. 3. InterpretML is a framework for training interpretable models and explaining black-box systems. DGL (Deep Graph Library) is a flexible framework designed for deep learning on graphs. ## What's the difference between this Python project and similar ones? Enumerate comparisons. These libraries are widely used for Explainable AI (XAI) and interpretable machine learning, distinguishing them from general-purpose ML libraries. DGL vs. Other DL Frameworks: DGL specializes in graph neural networks (GNNs), unlike PyTorch or TensorFlow, which focus on general deep learning. Anyone who agrees with this pull request could submit an *Approve* review to it. --- <sub>🔄 This issue represents a GitHub Pull Request. It cannot be merged through Gitea due to API limitations.</sub>

GiteaMirror added the pull-request label 2025-11-06 13:27:01 -06:00

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Reference: github-starred/awesome-python#1979