Interpretable Machine Learning Python Packages

interpret-core

Fit interpretable models. Explain blackbox machine learning.

interpret

Fit interpretable models. Explain blackbox machine learning.

aplr

APLR builds predictive, interpretable regression and classification models using Automatic Piecewise Linear Regression. It often rivals tree-based methods in predictive accuracy while offering smoother and interpretable predictions.

dice-ml

Generate Diverse Counterfactual Explanations for any machine learning model.

dalex

moDel Agnostic Language for Exploration and eXplanation

shapiq

Shapley Interactions and Shapley Values for Machine Learning

piml

PiML (Python Interpretable Machine Learning) toolbox for model development & diagnostics

xaisuite

XAISuite: Train machine learning models, generate explanations, and compare different explanation systems with just a simple line of code.

pyaerial

Scalable association rule mining from tabular datasets.

pyss3

A Python library for Interpretable Machine Learning in Text Classification using the SS3 model, with easy-to-use visualization tools for Explainable AI :octocat:

torch-explain

PyTorch Explain: Interpretable Deep Learning in Python.

lirisimpact

Repository contaning the original code of IMPACT algorithm, an interpretable model for ordinal predictions with multi-class outputs"

omnixai

OmniXAI: An Explainable AI Toolbox

explainx

Explain and debug any black-box Machine Learning model.

snore-embedding

SNoRe: Scalable Unsupervised Learning of Symbolic Node Representations

xpotato

XAI based human-in-the-loop framework for automatic rule-learning.

midlearn

A scikit-learn compatible Python wrapper of the midr R package

visualime

Implementation of LIME focused on producing user-centric local explanations for image classifiers.

zennit-crp

An eXplainable AI toolkit with Concept Relevance Propagation and Relevance Maximization

pytsetlinmachineparallel

Multi-threaded implementation of the Tsetlin Machine, Convolutional Tsetlin Machine, Regression Tsetlin Machine, and Weighted Tsetlin Machine, with support for continuous features and multigranularity.

powerlift

Fit interpretable models. Explain blackbox machine learning.

slise

Robust regression algorithm that can be used for explaining black box models (Python implementation)

survlimepy

Local interpretability for survival models

layerssustainabilityanalysis

A Python library that analyzes the layer sustainability of neural networks