moDel Agnostic Language for Exploration and eXplanation
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Updated
Oct 2, 2024 - Python
moDel Agnostic Language for Exploration and eXplanation
Workshop: Explanation and exploration of machine learning models with R and DALEX at eRum 2020
Documentation for the DALEX project
This is a repository for reproducibility purposes. In this research, a large number of datasets were used to create different ML models, which were then explained by XAI measures. Seeking to identify situations where XAI measures agreed or disagreed with each other.
Robustness of Global Feature Effect Explanations (ECML PKDD 2024)
Building binary predictors on a heavily imbalanced dataset - exercise on policy cross-selling [kaggle]
Elements of my term paper in Data Mining 2 at Faculty of Mathematics, University of Belgrade.
Efficient and Accurate Explanation Estimation with Distribution Compression (ICML 2024 Workshops)
Multi-class classification of drug resistance in MTB clinical isolates
A data science summer project with James Bond movies data.
This project predicts whether an individual earns more than 50K using the Adult Income dataset. A Random Forest model is trained and evaluated, with explanations provided through DALEX and LIME for feature importance and model transparency.
This is a repository for reproducibility purposes. In this research, a large number of datasets were used to create different ML models, which were then explained by XAI measures. Proposing a new measure of XAI called eXirt.
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