1. Arrhythmia: Distinguish between the presence and absence of cardiac arrhythmia and classify it in one of the 16 groups.
2. Musk (Version 1): The goal is to learn to predict whether new molecules will be musks or non-musks
3. Low Resolution Spectrometer: From IRAS data -- NASA Ames Research Center
4. Arcene: ARCENE's task is to distinguish cancer versus normal patterns from mass-spectrometric data. This is a two-class classification problem with continuous input variables. This dataset is one of 5 datasets of the NIPS 2003 feature selection challenge.
5. MicroMass: A dataset to explore machine learning approaches for the identification of microorganisms from mass-spectrometry data.
6. PEMS-SF: 15 months worth of daily data (440 daily records) that describes the occupancy rate, between 0 and 1, of different car lanes of the San Francisco bay area freeways across time.
7. Northix: Northix is designed to be a schema matching benchmark problem for data integration of two entity relationship databases.