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14 search results found

Shapash ⭐ 2,547

🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models

Shap Hypetune ⭐ 496

A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models.

Automated Tool for Optimized Modelling

Timeshap ⭐ 127

TimeSHAP explains Recurrent Neural Network predictions.

Survshap ⭐ 65

SurvSHAP(t): Time-dependent explanations of machine learning survival models

Fooling Lime Shap ⭐ 47

Adversarial Attacks on Post Hoc Explanation Techniques (LIME/SHAP)

Model Interpretation ⭐ 16

Overview of different model interpretability libraries.

Xai Tool4gee ⭐ 16

A Colab notebook for land cover mapping and monitoring using Earth Engine

Explainableml Vision ⭐ 14

This repository introduces different Explainable AI approaches and demonstrates how they can be implemented with PyTorch and torchvision. Used approaches are Class Activation Mappings, LIMA and SHapley Additive exPlanations.

Working Women ⭐ 11

Code for the paper 'Working Women and Caste in India' (ICLR 2019 AI for Social Good Workshop)

Wavemap_paper ⭐ 7

This repo allows for the complete reproduction, from processed data, of all the main and supplemental figures in the manuscript Non-linear Dimensionality Reduction on Extracellular Waveforms Reveals Physiological, Functional, and Laminar Diversity in Premotor Cortex.

Onconetexplainer ⭐ 6

OncoNetExplainer: Explainable Prediction of Cancer Types Based on Gene Expression Data

Python package providing a minimal implementation of the SHAP algorithm using the Kernel method

Streamlit Shap Explorer ⭐ 5

A Streamlit Web Application that predicts the genre of a song, interactively explores the corresponding SHAP values and locally explains a CatBoost Multi Classification model

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