Welcome to the KEEL-dataset repository

In this section you can find and download all the datasets from KEEL-dataset repository. Please, if you use any of them, cite us using the following reference:

KEEL-dataset citation paper: J. Alcalá-Fdez, A. Fernandez, J. Luengo, J. Derrac, S. García, L. Sánchez, F. Herrera. KEEL Data-Mining Software Tool: Data Set Repository, Integration of Algorithms and Experimental Analysis Framework. Journal of Multiple-Valued Logic and Soft Computing 17:2-3 (2011) 255-287.

This page aims at providing to the machine learning researchers a set of benchmarks to analyze the behavior of the learning methods. Concretely, it is possible to find benchmarks already formatted in KEEL format for classification (such as standard, multi instance or imbalanced data), semi-supervised classification, regression, time series and unsupervised learning. Also, a set of low quality data benchmarks is maintained in the repository.

From these pages, any researcher can download any data set exposed. Apart from the original data, some extra contents are provided (data already partitioned in several formats, data descriptions ...). Moreover, for each category we show some relevant research papers in which these data sets have been employed. Any researcher can obtain, from each one, the complete set of data employed to perform the experimental study and the results achieved.