Paper for 2018 Joint Statistical Meetings: https://ww2.amstat.org/meetings/jsm/2018/onlineprogram/AbstractDetails.cfm?abstractid=329539
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Updated
Dec 7, 2018 - TeX
Paper for 2018 Joint Statistical Meetings: https://ww2.amstat.org/meetings/jsm/2018/onlineprogram/AbstractDetails.cfm?abstractid=329539
Local Interpretable (Model-agnostic) Visual Explanations - model visualization for regression problems and tabular data based on LIME method. Available on CRAN
Slides, videos and other potentially useful artifacts from various presentations on responsible machine learning.
Implementation of the Anchors algorithm: Explain black-box ML models
Article for Special Edition of Information: Machine Learning with Python
An R package for computing asymmetric Shapley values to assess causality in any trained machine learning model
Show case for modelStudio based on ⚽⚽⚽FIFA 20 ⚽⚽⚽
Variable importance via oscillations
Data generator for Arena - interactive XAI dashboard
H2O.ai Machine Learning Interpretability Resources
A java project made in january as an Upgrad assignment using servlet-jsp
XMLX GitHub configuration
The code of AAAI 2020 paper "Transparent Classification with Multilayer Logical Perceptrons and Random Binarization".
A Julia package for interpretable machine learning with stochastic Shapley values
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