1. Wearable Computing: Classification of Body Postures and Movements (PUC-Rio): A dataset with 5 classes (sitting-down, standing-up, standing, walking, and sitting) collected on 8 hours of activities of 4 healthy subjects. We also established a baseline performance index.
2. Wall-Following Robot Navigation Data: The data were collected as the SCITOS G5 robot navigates through the room following the wall in a clockwise direction, for 4 rounds, using 24 ultrasound sensors arranged circularly around its 'waist'.
3. UJIIndoorLoc-Mag: The UJIIndoorLoc-Mag is an indoor localization database to test Indoor Positioning System that rely on Earth's magnetic field variations.
4. Spambase: Classifying Email as Spam or Non-Spam
5. SML2010: This dataset is collected from a monitor system mounted in a domotic house. It corresponds to approximately 40 days of monitoring data.
6. Restaurant & consumer data: The dataset was obtained from a recommender system prototype. The task was to generate a top-n list of restaurants according to the consumer preferences.
7. Planning Relax: The dataset concerns with the classification of two mental stages from recorded EEG signals: Planning (during imagination of motor act) and Relax state.
8. Pen-Based Recognition of Handwritten Digits: Digit database of 250 samples from 44 writers
9. PAMAP2 Physical Activity Monitoring: The PAMAP2 Physical Activity Monitoring dataset contains data of 18 different physical activities, performed by 9 subjects wearing 3 inertial measurement units and a heart rate monitor.
10. Page Blocks Classification: The problem consists of classifying all the blocks of the page layout of a document that has been detected by a segmentation process.
11. Optical Recognition of Handwritten Digits: Two versions of this database available; see folder
12. Online Video Characteristics and Transcoding Time Dataset: The dataset contains a million randomly sampled video instances listing 10 fundamental video characteristics along with the YouTube video ID.
13. MHEALTH Dataset: The MHEALTH (Mobile Health) dataset is devised to benchmark techniques dealing with human behavior analysis based on multimodal body sensing.
14. Letter Recognition: Database of character image features; try to identify the letter
15. Leaf: This dataset consists in a collection of shape and texture features extracted from digital images of leaf specimens originating from a total of 40 different plant species.
16. KDD Cup 1999 Data: This is the data set used for The Third International Knowledge Discovery and Data Mining Tools Competition, which was held in conjunction with KDD-99
17. Internet Usage Data: This data contains general demographic information on internet users in 1997.
18. Heterogeneity Activity Recognition Data Set: The Heterogeneity Dataset for Human Activity Recognition from Smartphone and Smartwatches is a dataset devised to benchmark human activity recognition containing sensor heterogeneities.
19. Grammatical Facial Expressions: This dataset supports the development of models that make possible to interpret Grammatical Facial Expressions from Brazilian Sign Language (Libras).
20. First-order theorem proving: Given a theorem, predict which of five heuristics will give the fastest proof when used by a first-order prover. A sixth prediction declines to attempt a proof, should the theorem be too difficult.
21. Educational Process Mining (EPM): A Learning Analytics Data Set: Educational Process Mining data set is built from the recordings of 115 subjects' activities through a logging application while learning with an educational simulator.
22. Dataset for Sensorless Drive Diagnosis: Features are extracted from motor current. The motor has intact and defective components. This results in 11 different classes with different conditions.
23. Condition Based Maintenance of Naval Propulsion Plants: Data have been generated from a sophisticated simulator of a Gas Turbines (GT), mounted on a Frigate characterized by a COmbined Diesel eLectric And Gas (CODLAG) propulsion plant type.
24. Concrete Slump Test: Concrete is a highly complex material. The slump flow of concrete is not only determined by the water content, but that is also influenced by other concrete ingredients.
25. Buzz in social media : This data-set contains examples of buzz events from two different social networks: Twitter, and Tom's Hardware, a forum network focusing on new technology with more conservative dynamics.