yramon / edc
Heuristic best-first algorithm for computing Evidence Counterfactuals (SEDC): explaining the model predictions of any classifier using a minimal set of features, such that removing these features results in a predicted class change.
☆15Updated 4 years ago
Alternatives and similar repositories for edc:
Users that are interested in edc are comparing it to the libraries listed below
- Model Agnostic Counterfactual Explanations☆87Updated 2 years ago
- Adversarial Attacks on Post Hoc Explanation Techniques (LIME/SHAP)☆82Updated 2 years ago
- Hybrid algorithm based on SEDC and LIME for computing Evidence Counterfactuals (LIME-Counterfactual): explaining the model predictions of…☆11Updated 4 years ago
- python tools to check recourse in linear classification☆76Updated 4 years ago
- CEML - Counterfactuals for Explaining Machine Learning models - A Python toolbox☆44Updated last week
- Modular Python Toolbox for Fairness, Accountability and Transparency Forensics☆77Updated last year
- Code repository for our paper "Failing Loudly: An Empirical Study of Methods for Detecting Dataset Shift": https://arxiv.org/abs/1810.119…☆104Updated last year
- CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms☆288Updated last year
- A toolbox for differentially private data generation☆131Updated last year
- A lightweight implementation of removal-based explanations for ML models.☆59Updated 3 years ago
- Multi-Objective Counterfactuals☆41Updated 2 years ago
- All about explainable AI, algorithmic fairness and more☆107Updated last year
- OpenXAI : Towards a Transparent Evaluation of Model Explanations☆245Updated 8 months ago
- A Natural Language Interface to Explainable Boosting Machines☆66Updated 9 months ago
- For calculating global feature importance using Shapley values.☆267Updated this week
- A Python package for unwrapping ReLU DNNs☆70Updated last year
- Contrastive Explanation (Foil Trees), developed at TNO/Utrecht University☆45Updated 2 years ago
- LOcal Rule-based Exlanations☆53Updated last year
- Code for using CDEP from the paper "Interpretations are useful: penalizing explanations to align neural networks with prior knowledge" ht…☆127Updated 4 years ago
- Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)☆128Updated 3 years ago
- Hands-on tutorial on ML Fairness☆71Updated last year
- Code accompanying the paper "Preserving Causal Constraints in Counterfactual Explanations for Machine Learning Classifiers"☆31Updated 2 years ago
- Clairvoyance: a Unified, End-to-End AutoML Pipeline for Medical Time Series☆132Updated 2 years ago
- Fair Empirical Risk Minimization (FERM)☆37Updated 4 years ago
- This repository contains the full code for the "Towards fairness in machine learning with adversarial networks" blog post.☆117Updated 4 years ago
- Supervised Local Modeling for Interpretability☆28Updated 6 years ago
- ☆35Updated last year
- XAI-Bench is a library for benchmarking feature attribution explainability techniques☆64Updated 2 years ago
- Tools for training explainable models using attribution priors.☆124Updated 4 years ago
- Unofficial Pytorch implementation of SAINT: Improved Neural Networks for Tabular Data via Row Attention and Contrastive Pretraining https…☆26Updated last year