Shap Python Packages

shap

A game theoretic approach to explain the output of any machine learning model.

explainerdashboard

Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models.

powershap

A power-full Shapley feature selection method.

shapiq

Shapley Interactions and Shapley Values for Machine Learning

fasttreeshap

Fast SHAP value computation for interpreting tree-based models

probatus

SHAP-based validation for linear and tree-based models. Applied to binary, multiclass and regression problems.

streamlit-shap

streamlit-shap provides a wrapper to display SHAP plots in Streamlit.

shapash

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

shap-hypetune

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

axon-quant

AI-native event-driven trading engine. Rust core with Python RL bindings. Built-in Gymnasium environments, LLM agents, SHAP explainability, and model ensembling — from backtesting to production.(AI 原生事件驱动交易引擎，Rust 内核，Python RL 绑定，支持 Gymnasium 环境、LLM 智能体、SHAP 可解释性与模型集成，贯穿回测到生产部署。)

xper

A methodology designed to measure the contribution of the features to the predictive performance of any econometric or machine learning model.

py-lucidum

Local-first browser workbench for exploring CSV and Parquet datasets with DuckDB, profiling, charts, UK maps, and optional GLM/GBM modelling.

nlp-shap

mllm-shap: Shapley-value explainability for conversational and multimodal language models.

quoptuna

Fairness-aware, explainable AutoML for quantum + classical ML — 21 models, one Optuna search, SHAP & AI reports. uvx quoptuna

datatypical

Scientific Data Significance Rankings with Shapley Explanations

shaperone

A game theoretic approach to explain the output of any machine learning model.

atom-ml

Automated Tool for Optimized Modelling

spml2-mltools

spml2-mltools is a convenient package for applying machine learning workflows with a Streamlit app, generating Excel outputs, and visualizations.

pandasflow

A set of custom python modules for friendly workflow on pandas

mllm-shap

mllm-shap: Shapley-value explainability for conversational and multimodal language models.

striders

Efficient surrogate-based model explanations (XAI) using landmark-based kernel approximations for scalable SHAP values

covenants

pytest for credit-model governance: test a credit model's documented claims (reason codes, monotonicity, features, exclusions) in CI.

timeshap

TimeSHAP explains Recurrent Neural Network predictions.

chessplainer

Explain chess positions with SHAP: which pieces make Stockfish think a position is winning, drawn or lost.