Combining Visualization and Verbalization for Interpretable Machine Learning
TeleGam is a prototype system that demonstrates how visualizations and verbalizations can collectively support interactive interpretation of machine learning models, for example, generalized additive models (GAMs).
For a live demo, visit: poloclub.github.io/telegam
Installation and Running Locally
Download or clone this repository:
git clone https://github.com/poloclub/telegam.git
Within the cloned repo, run a web server:
python -m http.server
MIT License. See
TeleGam: Combining Visualization and Verbalization for Interpretable Machine Learning
Fred Hohman, Arjun Srinivasan, Steven Drucker
IEEE Visualization Conference (VIS). Vancouver, Canada, 2019.
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