Label Ranking Datasets
Semi-Synthetic
| Dataset |
type |
# Instances |
# Attributes |
# Labels |
| authorship |
A |
841 |
70 |
4 |
| bodyfat |
B |
252 |
7 |
7 |
| calhousing |
B |
20640 |
4 |
4 |
| cpu-small |
B |
8192 |
6 |
5 |
| elevators |
B |
16599 |
9 |
9 |
| fried |
B |
40769 |
9 |
5 |
| glass |
A |
214 |
9 |
6 |
| housing |
B |
506 |
6 |
6 |
| iris |
A |
150 |
4 |
3 |
| pendigits |
A |
10992 |
16 |
10 |
| segment |
A |
2310 |
18 |
7 |
| stock |
B |
950 |
5 |
5 |
| vehicle |
A |
846 |
18 |
4 |
| vowel |
A |
528 |
10 |
11 |
| wine |
A |
178 |
13 |
3 |
| wisconsin |
B |
194 |
16 |
16 |
Download (in .zip)
If you find these datasets useful, please cite the following work, where the datasets were introduced:
-
Weiwei Cheng, Jens Hühn, Eyke Hüllermeier
Decision tree and instance-based learning for label ranking [pdf][bibtex][slides][poster][video]
Proceedings of the 26th International Conference on Machine Learning
(ICML-09): 161-168, Omnipress
Montreal, Canada, June 2009
- Weiwei Cheng, Krzysztof Dembczyński, Eyke Hüllermeier
Label ranking methods based on the Plackett-Luce model [pdf][bibtex][slides][poster]
Proceedings of the 27th International Conference on Machine Learning
(ICML-10): 215-222, Omnipress
Haifa, Israel, June 2010
Real-World
| Dataset |
# Instances |
# Attributes |
# Labels |
| spo |
2465 |
24 |
11 |
| heat |
2465 |
24 |
6 |
| dtt |
2465 |
24 |
4 |
| cold |
2465 |
24 |
4 |
| diau |
2465 |
24 |
7 |
Download (in .zip)
If you find these datasets useful, please cite the following work, where the datasets were introduced:
-
Eyke Hüllermeier, Johannes Fürnkranz, Weiwei Cheng, Klaus Brinker
Label ranking by learning pairwise preferences [pdf][bibtex]
Artificial Intelligence 172: 1897-1916, Elsevier
|