Monotone Learning Datasets
The purpose of this dataset collection is to provide a test bed for monotone classifiers. The original data were collected from various resources, such as UCI and WEKA. A general preprocessing procedure was applied, taking the following aspects into consideration:
- Instances with missing values are ignored.
- Nominal values are transformed to numeric ones, according to the semantic.
- Features are normalized between 0 and 1.
- Datasets are formatted as .csv files with the class information in the last column.
We are consistently searching for real-world monotone learning datasets. If you have anything in mind, please do not hesitate to contact Weiwei Cheng.
| Dataset | # Instances | # Features | # Classes |
| breast cancer | 278 | 7 | 2 |
| car evaluation | 1728 | 6 | 4 |
| car mpg | 392 | 7 | 36 |
| cpu | 209 | 6 | 4 |
| den bosch | 119 | 8 | 2 |
| employee rejection acceptance (ERA) | 1000 | 4 | 4 |
| employee selection (ESL) | 488 | 4 | 9 |
| journal ranking | 172 | 5 | 4 |
| lectures evaluation (LEV) | 1000 | 4 | 5 |
| mammographic | 830 | 6 | 2 |
| social workers decisions (SWD) | 1000 | 10 | 4 |
Download (in .zip-format)
These datasets have been used in:
- Ali Fallah Tehrani, Weiwei Cheng, Eyke Hüllermeier
Choquistic regression: generalizing logistic regression using the Choquet integral [pdf][bibtex][slides]
Proceedings of the 7th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT-2011): 868-875, Atlantis Press
Aix-les-Bains, France, July 2011 Nomination for Best Student Paper Award
- Ali Fallah Tehrani, Weiwei Cheng, Eyke Hüllermeier
Preference learning using the Choquet integral: the case of multipartite ranking [pdf][bibtex]
Proceedings of the 20th Workshop Computational Intelligence (WCI-10): 119-130, KIT Scientific Publishing
Dortmund, Germany, December 2010
