Abstract
Bayesian approaches to color category learning formalize learning as a problem of Bayesian inference, requiring the learner to form generalizations that go beyond observed examples of members of a category. This formal framework can be used to make predictions about both individual judgments and how populations form color categories.
| Original language | English (US) |
|---|---|
| Title of host publication | Encyclopedia of Color Science and Technology |
| Publisher | Springer New York |
| Pages | 74-77 |
| Number of pages | 4 |
| ISBN (Electronic) | 9781441980717 |
| ISBN (Print) | 9781441980700 |
| State | Published - Jan 1 2016 |
| Externally published | Yes |
All Science Journal Classification (ASJC) codes
- General Physics and Astronomy
- General Engineering
- General Business, Management and Accounting
- General Chemical Engineering