andreArtelt / ceml
CEML - Counterfactuals for Explaining Machine Learning models - A Python toolbox
☆43Updated 8 months ago
Alternatives and similar repositories for ceml:
Users that are interested in ceml are comparing it to the libraries listed below
- Model Agnostic Counterfactual Explanations☆88Updated 2 years ago
- A lightweight implementation of removal-based explanations for ML models.☆59Updated 3 years ago
- A collection of algorithms of counterfactual explanations.☆50Updated 4 years ago
- Code accompanying the paper "Preserving Causal Constraints in Counterfactual Explanations for Machine Learning Classifiers"☆30Updated 2 years ago
- XAI-Bench is a library for benchmarking feature attribution explainability techniques☆63Updated 2 years ago
- CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms☆286Updated last year
- Code to reproduce our paper on probabilistic algorithmic recourse: https://arxiv.org/abs/2006.06831☆36Updated 2 years ago
- Adversarial Attacks on Post Hoc Explanation Techniques (LIME/SHAP)☆82Updated 2 years ago
- Neural Additive Models (Google Research)☆69Updated 3 years ago
- Contrastive Explanation (Foil Trees), developed at TNO/Utrecht University☆45Updated 2 years ago
- For calculating Shapley values via linear regression.☆67Updated 3 years ago
- Multi-Objective Counterfactuals☆41Updated 2 years ago
- python tools to check recourse in linear classification☆75Updated 4 years ago
- Python package to compute interaction indices that extend the Shapley Value. AISTATS 2023.☆17Updated last year
- Rule Extraction Methods for Interactive eXplainability☆43Updated 2 years ago
- Fast and incremental explanations for online machine learning models. Works best with the river framework.☆54Updated 3 months ago
- A repo for transfer learning with deep tabular models☆102Updated 2 years ago
- Modular Python Toolbox for Fairness, Accountability and Transparency Forensics☆77Updated last year
- A Python package for unwrapping ReLU DNNs☆70Updated last year
- All about explainable AI, algorithmic fairness and more☆107Updated last year
- Testing Language Models for Memorization of Tabular Datasets.☆33Updated 2 months ago
- Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine Learning (AISTATS 2022 Oral)☆40Updated 2 years ago
- A Natural Language Interface to Explainable Boosting Machines☆65Updated 9 months ago
- Code for "NODE-GAM: Neural Generalized Additive Model for Interpretable Deep Learning"☆43Updated 2 years ago
- Official code repository to the corresponding paper.☆29Updated last year
- Codes for reproducing the contrastive explanation in “Explanations based on the Missing: Towards Contrastive Explanations with Pertinent…☆54Updated 6 years ago
- Achieve error-rate fairness between societal groups for any score-based classifier.☆17Updated 11 months ago
- OpenXAI : Towards a Transparent Evaluation of Model Explanations☆243Updated 7 months ago
- Influence Estimation for Gradient-Boosted Decision Trees☆27Updated 10 months ago
- Training and evaluating NBM and SPAM for interpretable machine learning.☆77Updated 2 years ago