tiagobotari / melime
Meaningful Local Explanation for Machine Learning Models
☆40Updated last year
Alternatives and similar repositories for melime:
Users that are interested in melime are comparing it to the libraries listed below
- R package for data complexity measures for imbalanced classification tasks☆9Updated 3 years ago
- Extended Complexity Library in R☆57Updated 4 years ago
- Meta-Feature Extractor☆28Updated 2 years ago
- Meta-Padawan solution to the NeurIPS (2021) - Few-shot learning competition.☆9Updated 3 years ago
- ☆15Updated 6 years ago
- Python Meta-Feature Extractor package.☆131Updated 8 months ago
- Post-hoc Nemenyi test for algorithm statistical comparison.☆21Updated 4 years ago
- Interesting resources related to Explainable Artificial Intelligence, Interpretable Machine Learning, Interactive Machine Learning, Human…☆73Updated 2 years ago
- Model Agnostic Counterfactual Explanations☆87Updated 2 years ago
- A lightweight implementation of removal-based explanations for ML models.☆58Updated 3 years ago
- An image meta-feature extractor for meta-learning tasks.☆12Updated last year
- Code repository for our paper "Failing Loudly: An Empirical Study of Methods for Detecting Dataset Shift": https://arxiv.org/abs/1810.119…☆103Updated 11 months ago
- ☆76Updated 5 months ago
- All about explainable AI, algorithmic fairness and more☆107Updated last year
- ACV is a python library that provides explanations for any machine learning model or data. It gives local rule-based explanations for any…☆99Updated 2 years ago
- Contrastive Explanation (Foil Trees), developed at TNO/Utrecht University☆45Updated 2 years ago
- ☆72Updated 10 months ago
- A Python package for unwrapping ReLU DNNs☆70Updated last year
- A toolbox for fair and explainable machine learning☆55Updated 8 months ago
- python tools to check recourse in linear classification☆75Updated 4 years ago
- Fast implementation of Venn-ABERS probabilistic predictors☆72Updated last year
- Adversarial Attacks on Post Hoc Explanation Techniques (LIME/SHAP)☆82Updated 2 years ago
- For calculating global feature importance using Shapley values.☆266Updated this week
- Public home of pycorels, the python binding to CORELS☆77Updated 4 years ago
- An automated machine learning tool aimed to facilitate AutoML research.☆96Updated 6 months ago
- A practical Active Learning python package with a strong focus on experiments.☆51Updated 2 years ago
- Fast and incremental explanations for online machine learning models. Works best with the river framework.☆54Updated 2 months ago
- Multi-Objective Counterfactuals☆41Updated 2 years ago
- Application of the LIME algorithm by Marco Tulio Ribeiro, Sameer Singh, Carlos Guestrin to the domain of time series classification☆95Updated last year
- CEML - Counterfactuals for Explaining Machine Learning models - A Python toolbox☆42Updated 7 months ago