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
- Hybrid algorithm based on SEDC and LIME for computing Evidence Counterfactuals (LIME-Counterfactual): explaining the model predictions of…☆11Updated 4 years ago
- A toolbox for differentially private data generation☆131Updated last year
- Model Agnostic Counterfactual Explanations☆87Updated 2 years ago
- Adversarial Attacks on Post Hoc Explanation Techniques (LIME/SHAP)☆82Updated 2 years ago
- CEML - Counterfactuals for Explaining Machine Learning models - A Python toolbox☆44Updated 2 weeks ago
- Modular Python Toolbox for Fairness, Accountability and Transparency Forensics☆77Updated last year
- Contrastive Explanation (Foil Trees), developed at TNO/Utrecht University☆45Updated 2 years ago
- Benchmarking synthetic data generation methods.☆273Updated this week
- Generative adversarial training for generating synthetic tabular data.☆288Updated 2 years ago
- 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
- All about explainable AI, algorithmic fairness and more☆107Updated last year
- A lightweight implementation of removal-based explanations for ML models.☆59Updated 3 years ago
- CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms☆288Updated last year
- Multi-Objective Counterfactuals☆41Updated 2 years ago
- python tools to check recourse in linear classification☆76Updated 4 years ago
- LOcal Rule-based Exlanations☆53Updated last year
- This repository contains the full code for the "Towards fairness in machine learning with adversarial networks" blog post.☆117Updated 4 years ago
- A Python package for unwrapping ReLU DNNs☆70Updated 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
- A repo for transfer learning with deep tabular models☆102Updated 2 years ago
- Explaining Anomalies Detected by Autoencoders Using SHAP☆41Updated 3 years ago
- Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)☆128Updated 3 years ago
- ☆13Updated 4 years ago
- A Natural Language Interface to Explainable Boosting Machines☆66Updated 10 months ago
- Generalized Optimal Sparse Decision Trees☆63Updated last year
- ☆76Updated 7 months ago
- ☆16Updated 4 years ago
- TimeSHAP explains Recurrent Neural Network predictions.☆174Updated last year
- For calculating global feature importance using Shapley values.☆268Updated this week
- Application of the LIME algorithm by Marco Tulio Ribeiro, Sameer Singh, Carlos Guestrin to the domain of time series classification☆95Updated last year