1. Balloons: Data previously used in cognitive psychology experiment; 4 data sets represent different conditions of an experiment
2. Challenger USA Space Shuttle O-Ring: Task: predict the number of O-rings that experience thermal distress on a flight at 31 degrees F given data on the previous 23 shuttle flights
3. COVID-19 Surveillance: Coronavirus Disease (COVID-19) Surveillance.
4. Gas sensor array under flow modulation: The data set contains 58 time series acquired from 16 chemical sensors under gas flow modulation conditions. The sensors were exposed to different gaseous binary mixtures of acetone and ethanol.
5. Lenses: Database for fitting contact lenses
6. Lung Cancer: Lung cancer data; no attribute definitions
7. Monolithic Columns in Troad and Mysia Region: These data have been constituted to clarify the distribution in Northwestern Anatolia of the monolithic columns produced in the ancient granite quarries located in Troad and Mysia Regions.
8. OCT data & Color Fundus Images of Left & Right Eyes: This dataset contains OCT data (in mat format) and color fundus data (in jpg format) of left & right eyes of 50 healthy persons.
9. Parkinson Disease Spiral Drawings Using Digitized Graphics Tablet: Handwriting database consists of 62 PWP(People with Parkinson) and 15 healthy individuals. Three types of recordings (Static Spiral Test, Dynamic Spiral Test and Stability Test) are taken.
10. Person Classification Gait Data: Gait is considered a biometric criterion. Therefore, we tried to classify people with gait analysis with this gait data set.
11. Post-Operative Patient: Dataset of patient features
12. SCADI: First self-care activities dataset based on ICF-CY.
13. Shuttle Landing Control: Tiny database; all nominal values
14. Soybean (Small): Michalski's famous soybean disease database
15. Sponge: Data on sponges; Attributes in spanish
16. StoneFlakes: Stone flakes are waste products of the stone tool production in
the prehistoric era. The variables are means of geometric and
stylistic features of the flakes contained in different inventories.
17. Trains: 2 data formats (structured, one-instance-per-line)
18. Vehicle routing and scheduling problems: Data collection was conducted through notes taken during the distribution of orders in a courier company that operates in the region and in the city of São Paulo (Brazil).