Commit 36712776 authored by ALVES Guilherme's avatar ALVES Guilherme
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Update README.md

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This project is an extension of LimeOut[1]. It aims at tackle process fairness for classification, while keeping the accuracy level (or improving).
More precisely, ExpOut incorporates different explainers.
Classifiers available:
* Multilayer Perceptron
* Logistic Regression
* Random Forest
* Bagging
* AdaBoost
* Gaussian Mixture
* Gradiente Boosting
Explainers
* LIME
* Anchors
# Example
`runner --data german.data --trainsize 0.8 --algo mlp --cat_features 0 2 3 5 6 8 9 11 13 14 16 18 19 --drop 8 18 19`
# References
[1] Vaishnavi Bhargava, Miguel Couceiro, Amedeo Napoli. LimeOut: An Ensemble Approach To Improve Process Fairness. 2020. ⟨hal-02864059v2⟩
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