Search 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.

omnixai

OmniXAI: An Explainable AI Toolbox

explainx

Explain and debug any black-box Machine Learning model.

lirisimpact

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

midlearn

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

xpotato

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

snore-embedding

SNoRe: Scalable Unsupervised Learning of Symbolic Node Representations

zennit-crp

An eXplainable AI toolkit with Concept Relevance Propagation and Relevance Maximization

visualime

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

slise

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

powerlift

Fit interpretable models. Explain blackbox machine learning.

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.

survlimepy

Local interpretability for survival models

random-subgroups

A machine learning python package for learning ensembles of subgroups for predictive tasks.