Neo: Generalizing Confusion Matrix Visualization to Hierarchical and Multi-Output Labels

Author:

Görtler Jochen1,Hohman Fred2,Moritz Dominik2,Wongsuphasawat Kanit2,Ren Donghao2,Nair Rahul3,Kirchner Marc3,Patel Kayur2

Affiliation:

1. University of Konstanz, Germany

2. Apple, United States

3. Apple, Germany

Publisher

ACM

Reference40 articles.

1. Visual Methods for Analyzing Probabilistic Classification Data

2. Bilal Alsallakh , Amin Jourabloo , Mao Ye , Xiaoming Liu , and Liu Ren . 2017. Do convolutional neural networks learn class hierarchy?IEEE Transactions on Visualization and Computer Graphics ( 2017 ). https://doi.org/10.1109/tvcg.2017.2744683 Bilal Alsallakh, Amin Jourabloo, Mao Ye, Xiaoming Liu, and Liu Ren. 2017. Do convolutional neural networks learn class hierarchy?IEEE Transactions on Visualization and Computer Graphics (2017). https://doi.org/10.1109/tvcg.2017.2744683

3. Bilal Alsallakh , Zhixin Yan , Shabnam Ghaffarzadegan , Zeng Dai , and Liu Ren . 2020 . Visualizing classification structure of large-scale classifiers . In ICML Workshop on Human Interpretability in Machine Learning. Bilal Alsallakh, Zhixin Yan, Shabnam Ghaffarzadegan, Zeng Dai, and Liu Ren. 2020. Visualizing classification structure of large-scale classifiers. In ICML Workshop on Human Interpretability in Machine Learning.

4. Software Engineering for Machine Learning: A Case Study

5. ModelTracker

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