tiagobotari / melime
Meaningful Local Explanation for Machine Learning Models
☆41Updated last year
Related projects: ⓘ
- R package for data complexity measures for imbalanced classification tasks☆9Updated 3 years ago
- Extended Complexity Library in R☆57Updated 3 years ago
- Meta-Feature Extractor☆28Updated 2 years ago
- Python Meta-Feature Extractor package.☆125Updated 2 months ago
- Code repository for our paper "Failing Loudly: An Empirical Study of Methods for Detecting Dataset Shift": https://arxiv.org/abs/1810.119…☆101Updated 5 months ago
- Meta-Padawan solution to the NeurIPS (2021) - Few-shot learning competition.☆9Updated 2 years ago
- A lightweight implementation of removal-based explanations for ML models.☆56Updated 3 years ago
- Model Agnostic Counterfactual Explanations☆86Updated last year
- Post-hoc Nemenyi test for algorithm statistical comparison.☆21Updated 4 years ago
- ☆68Updated 4 months ago
- ☆14Updated 5 years ago
- Interesting resources related to Explainable Artificial Intelligence, Interpretable Machine Learning, Interactive Machine Learning, Human…☆69Updated last year
- Contrastive Explanation (Foil Trees), developed at TNO/Utrecht University☆45Updated last year
- ☆68Updated 2 weeks ago
- Fast implementation of Venn-ABERS probabilistic predictors☆69Updated 7 months ago
- Adversarial Attacks on Post Hoc Explanation Techniques (LIME/SHAP)☆75Updated last year
- Public home of pycorels, the python binding to CORELS☆72Updated 4 years ago
- ACV is a python library that provides explanations for any machine learning model or data. It gives local rule-based explanations for any…☆103Updated 2 years ago
- All about explainable AI, algorithmic fairness and more☆107Updated 11 months ago
- An image meta-feature extractor for meta-learning tasks.☆12Updated 10 months ago
- A practical Active Learning python package with a strong focus on experiments.☆51Updated last year
- Multi-Objective Counterfactuals☆40Updated 2 years ago
- A Python package for unwrapping ReLU DNNs☆70Updated 8 months ago
- WeightedSHAP: analyzing and improving Shapley based feature attributions (NeurIPS 2022)☆161Updated last year
- Expanding Explainable K-Means Clustering☆90Updated last year
- A toolbox for fair and explainable machine learning☆52Updated 3 months ago
- A repo for transfer learning with deep tabular models☆100Updated last year
- An automated machine learning tool aimed to facilitate AutoML research.☆92Updated 2 weeks ago
- XAI-Bench is a library for benchmarking feature attribution explainability techniques☆55Updated last year
- Repository for code release of paper "Robust Variational Autoencoders for Outlier Detection and Repair of Mixed-Type Data" (AISTATS 2020)☆49Updated 4 years ago