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captum

Model interpretability and understanding for PyTorch

shapiq

Shapley Interactions and Shapley Values for Machine Learning

lofo-importance

Leave One Feature Out Importance

pytolemaic

Toolbox for analysis of model's quality and model's description. For further details see

dominance-analysis

This package can be used for dominance analysis or Shapley Value Regression for finding relative importance of predictors on given dataset. This library can be used for key driver analysis or marginal resource allocation models.

msdlib

This is a custom library for data processing, visualization and machine learning tools.

mlfeatureselection

Features selector based on the self selected-algorithm, loss function and validation method

xai

XAI - An industry-ready machine learning library that ensures explainable AI by design

target-permutation-importances

A Python Package that computes Target Permutation Importances (Null Importances) of a machine learning model.

featureranker

Python package for feature ranking

shapley-lz

Computes the Shapley Lorenz Zonoid share of a set of covariates

dime-xai

Implementation of Dual Interpretable Model-agnostic Explanations for Rasa DIET classifiers

lorenz-zonoid

Computes the Shapley Lorenz Zonoid share of covariates

acd

Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)

dnn-inference

Significance tests of feature relevance for a black-box learner

tanml

Automated validation toolkit for tabular ML models in finance and regulated domains.

fippy

Model-Agnostic Feature Importance in Python