98 citations · 260 across the 9 of their papers we have counts for
9 papers
RuleExplorer: A Scalable Matrix Visualization for Understanding Tree Ensemble Classifiers
Zhen Li, Weikai Yang, Jun Yuan +6
The high performance of tree ensemble classifiers benefits from a large set of rules, which, in turn, makes the models hard to understand. To improve interpretability, existing met…
DeHumor: Visual Analytics for Decomposing Humor
Xingbo Wang, Yao Ming, Tongshuang Wu +3
Despite being a critical communication skill, grasping humor is challenging -- a successful use of humor requires a mixture of both engaging content build-up and an appropriate voc…
GNNLens: A Visual Analytics Approach for Prediction Error Diagnosis of Graph Neural Networks
Zhihua Jin, Yong Wang, Qianwen Wang +3
Graph Neural Networks (GNNs) aim to extend deep learning techniques to graph data and have achieved significant progress in graph analysis tasks (e.g., node classification) in rece…
DECE: Decision Explorer with Counterfactual Explanations for Machine Learning Models
Furui Cheng, Yao Ming, Huamin Qu
With machine learning models being increasingly applied to various decision-making scenarios, people have spent growing efforts to make machine learning models more transparent and…
Interpretable and Steerable Sequence Learning via Prototypes
Yao Ming, Panpan Xu, Huamin Qu +1
One of the major challenges in machine learning nowadays is to provide predictions with not only high accuracy but also user-friendly explanations. Although in recent years we have…
Learning Vis Tools: Teaching Data Visualization Tutorials
Leo Yu-Ho Lo, Yao Ming, Huamin Qu
Teaching and advocating data visualization are among the most important activities in the visualization community. With growing interest in data analysis from business and science…