Abstract
We recall two previously-proposed notions of asymptotic calibration for a forecaster making a sequence of probability predictions. We note that the existence of efficient algorithms for calibrated forecasting holds only in the case of binary outcomes. We pose the question: do there exist such efficient algorithms for the general (non-binary) case?
| Original language | English |
|---|---|
| Pages (from-to) | 809-811 |
| Number of pages | 3 |
| Journal | Journal of Machine Learning Research |
| Volume | 19 |
| State | Published - 2011 |
| Event | 24th International Conference on Learning Theory, COLT 2011 - Budapest, Hungary Duration: 9 Jul 2011 → 11 Jul 2011 |
All Science Journal Classification (ASJC) codes
- Software
- Artificial Intelligence
- Control and Systems Engineering
- Statistics and Probability