1. 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
2. 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.
3. Gastrointestinal Lesions in Regular Colonoscopy: This dataset contains features extracted from colonoscopy videos used to detect gastrointestinal lesions. It contains 76 lesions: 15 serrated adenomas, 21 hyperplastic lesions and 40 adenoma.
4. Improved Spiral Test Using Digitized Graphics Tablet for Monitoring Parkinson’s Disease: Handwriting database consists of 25 PWP(People with Parkinson) and 15 healthy individuals.Three types of recordings (Static Spiral Test, Dynamic Spiral Test and Stability Test) are taken.
5. Lung Cancer: Lung cancer data; no attribute definitions
6. 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.
7. 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.
8. Predict keywords activities in a online social media: The data from Twitter was collected during 360 consecutive days. It was done by querying 1497 English keywords sampled from Wikipedia. This dataset is proposed in a Learning to rank setting.
9. 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.