A game theoretic approach to explain the output of any machine learning model.
created at Nov. 22, 2016, 7:17 p.m.
241 +1
21,966 +40
3,198 +4
Source code/webpage/demos for the What-If Tool
created at Sept. 7, 2018, 8:26 p.m.
29 +0
891 +1
166 +2
XAI - An eXplainability toolbox for machine learning
created at Jan. 11, 2019, 8 p.m.
44 +0
1,074 +3
161 +1
🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models
created at April 29, 2020, 7:34 a.m.
36 +0
2,671 +1
326 +1