MarcelRobeer / ContrastiveExplanationLinks
Contrastive Explanation (Foil Trees), developed at TNO/Utrecht University
☆44Updated 2 years ago
Alternatives and similar repositories for ContrastiveExplanation
Users that are interested in ContrastiveExplanation are comparing it to the libraries listed below
Sorting:
- All about explainable AI, algorithmic fairness and more☆110Updated last year
- Model Agnostic Counterfactual Explanations☆87Updated 2 years ago
- A simple, extensible library for developing AutoML systems☆175Updated 2 years ago
- A lightweight implementation of removal-based explanations for ML models.☆58Updated 4 years ago
- Code repository for our paper "Failing Loudly: An Empirical Study of Methods for Detecting Dataset Shift": https://arxiv.org/abs/1810.119…☆105Updated last year
- A Python package for unwrapping ReLU DNNs☆70Updated last year
- python tools to check recourse in linear classification☆77Updated 4 years ago
- Measure and visualize machine learning model performance without the usual boilerplate.☆97Updated 10 months ago
- Modular Python Toolbox for Fairness, Accountability and Transparency Forensics☆77Updated 2 years ago
- This repository contains the full code for the "Towards fairness in machine learning with adversarial networks" blog post.☆118Updated 4 years ago
- Meaningful Local Explanation for Machine Learning Models☆41Updated 2 years ago
- ⏸ Parallelized hyper-param optimization with validation set, not crossval☆90Updated 2 years ago
- ☆124Updated 4 years ago
- Practical ideas on securing machine learning models☆36Updated 4 years ago
- CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms☆292Updated last year
- Supervised Local Modeling for Interpretability☆29Updated 6 years ago
- Python Meta-Feature Extractor package.☆133Updated last year
- A practical Active Learning python package with a strong focus on experiments.☆51Updated 2 years ago
- A library that implements fairness-aware machine learning algorithms☆126Updated 4 years ago
- To Trust Or Not To Trust A Classifier. A measure of uncertainty for any trained (possibly black-box) classifier which is more effective t…☆177Updated 2 years ago
- This is a public collection of papers related to machine learning model interpretability.☆26Updated 3 years ago
- Preprint/draft article/blog on some explainable machine learning misconceptions. WIP!☆28Updated 6 years ago
- The official implementation of "The Shapley Value of Classifiers in Ensemble Games" (CIKM 2021).☆220Updated 2 years ago
- An automated machine learning tool aimed to facilitate AutoML research.☆99Updated 11 months ago
- CEML - Counterfactuals for Explaining Machine Learning models - A Python toolbox☆44Updated 2 months ago
- Application of the LIME algorithm by Marco Tulio Ribeiro, Sameer Singh, Carlos Guestrin to the domain of time series classification☆96Updated last year
- CostSensitiveClassification Library in Python☆206Updated 5 years ago
- Comparing fairness-aware machine learning techniques.☆159Updated 2 years ago
- A library for composing end-to-end tunable machine learning pipelines.☆120Updated 6 months ago
- General Interpretability Package☆58Updated 2 years ago