1. Trains: 2 data formats (structured, one-instance-per-line) 2. Sponge: Data on sponges; Attributes in spanish 3. Soybean (Small): Michalski's famous soybean disease database 4. 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. 5. Pedal Me Bicycle Deliveries: A dataset of weekly bicycle package deliveries by Pedal Me in London during 2020 and 2021. Nodes in the graph represent geographical units and edges are proximity based mutual adjacency relationships. 6. Non verbal tourists data: This dataset contains the information about non-verbal preferences of tourists 7. Multi-view Brain Networks: Multi-layer brain network datasets derived from the resting-state electroencephalography (EEG) data. 8. 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. 9. 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. 10. Lung Cancer: Lung cancer data; no attribute definitions 11. Labor Relations: From Collective Bargaining Review 12. Discrete Tone Image Dataset: Discrete Tone Images(DTI)are available which needs to be analyzed in detail. Here, we created this dataset for those who do research in DTI.
13. Daily Demand Forecasting Orders: The dataset was collected during 60 days, this is a real database of a brazilian logistics company. 14. Chemical Composition of Ceramic Samples: Classify ceramic samples based on their chemical composition from energy dispersive X-ray fluorescence 15. Cervical Cancer Behavior Risk: The dataset contains 19 attributes regarding ca cervix behavior risk with class label is ca_cervix with 1 and 0 as values which means the respondent with and without ca cervix, respectively. | 
