1. Character Trajectories: Multiple, labelled samples of pen tip trajectories recorded whilst writing individual characters. All samples are from the same writer, for the purposes of primitive extraction. Only characters with a single pen-down segment were considered. 2. Energy efficiency: This study looked into assessing the heating load and cooling load requirements of buildings (that is, energy efficiency) as a function of building parameters. 3. Gas Sensor Array Drift Dataset: This archive contains 13910 measurements from 16 chemical sensors utilized in simulations for drift compensation in a discrimination task of 6 gases at various levels of concentrations. 4. Gisette: GISETTE is a handwritten digit recognition problem. The problem is to separate the highly confusible digits '4' and '9'. This dataset is one of five datasets of the NIPS 2003 feature selection challenge.
5. ISOLET: Goal: Predict which letter-name was spoken--a simple classification task. 6. Letter Recognition: Database of character image features; try to identify the letter 7. Multiple Features: This dataset consists of features of handwritten numerals (`0'--`9') extracted from a collection of Dutch utility maps 8. Nomao: Nomao collects data about places (name, phone, localization...) from many sources.
Deduplication consists in detecting what data refer to the same place.
Instances in the dataset compare 2 spots. 9. Northix: Northix is designed to be a schema matching benchmark problem for data integration of two entity relationship databases. 10. Online Handwritten Assamese Characters Dataset: This is a dataset of 8235 online handwritten assamese characters. The “online” process involves capturing of data as text is written on a digitizing tablet with an electronic pen. 11. OPPORTUNITY Activity Recognition: The OPPORTUNITY Dataset for Human Activity Recognition from Wearable, Object, and Ambient Sensors is a dataset devised to benchmark human activity recognition algorithms (classification, automatic data segmentation, sensor fusion, feature extraction, etc). 12. Optical Recognition of Handwritten Digits: Two versions of this database available; see folder 13. 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. 14. 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. 15. 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. 16. Pen-Based Recognition of Handwritten Digits: Digit database of 250 samples from 44 writers 17. 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. 18. Reuter_50_50: The dataset is used for authorship identification in online Writeprint which is a new research field of pattern recognition. 19. SECOM: Data from a semi-conductor manufacturing process 20. Semeion Handwritten Digit: 1593 handwritten digits from around 80 persons were scanned, stretched in a rectangular box 16x16 in a gray scale of 256 values. 21. Skin Segmentation: The Skin Segmentation dataset is constructed over B, G, R color space. Skin and Nonskin dataset is generated using skin textures from face images of diversity of age, gender, and race people. 22. SMS Spam Collection: The SMS Spam Collection is a public set of SMS labeled messages that have been collected for mobile phone spam research. 23. Spambase: Classifying Email as Spam or Non-Spam 24. UJI Pen Characters: Data consists of written characters in a UNIPEN-like format 25. UJI Pen Characters (Version 2): A pen-based database with more than 11k isolated handwritten characters 26. URL Reputation: Anonymized 120-day subset of the ICML-09 URL data containing 2.4 million examples and 3.2 million features. 27. 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'. | 
