Label ranking by learning pairwise preferences
Artificial Intelligence
Enhancing artificial intelligence on a real mobile game
International Journal of Computer Games Technology - Artificial Intelligence for Computer Games
Preferential text classification: learning algorithms and evaluation measures
Information Retrieval
Mining ranking models from dynamic network data
MLDM'12 Proceedings of the 8th international conference on Machine Learning and Data Mining in Pattern Recognition
| Hi-index | 0.00 |
The preference model introduced in this paper gives a natural framework and a principled solution for a broad class of supervised learning problems with structured predictions, such as predicting orders (label and instance ranking), and predicting rates (classification and ordinal regression). We show how all these problems can be cast as linear problems in an augmented space, and we propose an on-line method to efficiently solve them. Experiments on an ordinal regression task confirm the effectiveness of the approach.