1.1k citations · 1.1k across the 2 of their papers we have counts for
2 papers
cs.LG2022★ 3 cited
Explanation of Machine Learning Models of Colon Cancer Using SHAP Considering Interaction Effects
Yasunobu Nohara, Toyoshi Inoguchi, Chinatsu Nojiri +1
When using machine learning techniques in decision-making processes, the interpretability of the models is important. Shapley additive explanation (SHAP) is one of the most promisi…
cs.LG2021★ 1.1k cited
Explanation of Machine Learning Models Using Shapley Additive Explanation and Application for Real Data in Hospital
Yasunobu Nohara, Koutarou Matsumoto, Hidehisa Soejima +1
When using machine learning techniques in decision-making processes, the interpretability of the models is important. In the present paper, we adopted the Shapley additive explanat…