20 citations · 68 across the 9 of their papers we have counts for
Showing stat.MLShow all
3 papers · 1 filter
stat.ML2024★ 2 cited
Inherently Interpretable Tree Ensemble Learning
Zebin Yang, Agus Sudjianto, Xiaoming Li +1
Tree ensemble models like random forests and gradient boosting machines are widely used in machine learning due to their excellent predictive performance. However, a high-performan…
stat.ML2020★ 16 cited
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…
stat.ML2019★ 8 cited
Enhancing Explainability of Neural Networks through Architecture Constraints
Zebin Yang, Aijun Zhang, Agus Sudjianto
Prediction accuracy and model explainability are the two most important objectives when developing machine learning algorithms to solve real-world problems. The neural networks are…