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Supporting User Interaction with Machine Learning through Interactive Visualizations
| Content Provider | Semantic Scholar |
|---|---|
| Author | Françoise, Jules Bevilacqua, Frédéric |
| Copyright Year | 2016 |
| Abstract | CHI’16 Workshop on Human-Centred Machine Learning, May 7–12, 2016, San Jose, CA, USA. Abstract This paper discusses novel visualizations that expose the behavior and internal values of machine learning models rather than their sole results. Interactive visualizations have the potential to shift the perception of machine learning models from black-box processes to transparent artifacts that can be experienced and crafted. We discuss how they can reveal the affordances of different techniques, and how they could lead to a deeper understanding of the underlying algorithms. We describe a proof-of-concept application to visualize and manipulate Hidden Markov Models, that provides a ground for a broader discussion on the potentials and challenges of interactive visualizations in humancentered machine learning. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.doc.gold.ac.uk/~mas02mg/HCML2016/HCML2016_paper_20.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
