83 citations · 308 across the 26 of their papers we have counts for
3 papers · 2 filters
Surrogate Locally-Interpretable Models with Supervised Machine Learning Algorithms
Linwei Hu, Jie Chen, Vijayan N. Nair +1
Supervised Machine Learning (SML) algorithms, such as Gradient Boosting, Random Forest, and Neural Networks, have become popular in recent years due to their superior predictive pe…
Adaptive Explainable Neural Networks (AxNNs)
Jie Chen, Joel Vaughan, Vijayan N. Nair +1
While machine learning techniques have been successfully applied in several fields, the black-box nature of the models presents challenges for interpreting and explaining the resul…
GAMI-Net: An Explainable Neural Network based on Generalized Additive Models with Structured Interactions
Zebin Yang, Aijun Zhang, Agus Sudjianto
The lack of interpretability is an inevitable problem when using neural network models in real applications. In this paper, an explainable neural network based on generalized addit…