1. Machine Learning based ZZAlpha Ltd. Stock Recommendations 2012-2014: The data here are the ZZAlpha® machine learning recommendations made for various US traded stock portfolios the morning of each day during the 3 year period Jan 1, 2012 - Dec 31, 2014. 2. Bar Crawl: Detecting Heavy Drinking: Accelerometer and transdermal alcohol content data from a college bar crawl. Used to predict heavy drinking episodes via mobile data. 3. Dataset for ADL Recognition with Wrist-worn Accelerometer: Recordings of 16 volunteers performing 14 Activities of Daily Living (ADL) while carrying a single wrist-worn tri-axial accelerometer. 4. Bar Crawl: Detecting Heavy Drinking: Accelerometer and transdermal alcohol content data from a college bar crawl. Used to predict heavy drinking episodes via mobile data. 5. 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. 6. Indoor User Movement Prediction from RSS data: This dataset contains temporal data from a Wireless Sensor Network deployed in real-world office environments. The task is intended as real-life benchmark in the area of Ambient Assisted Living. 7. Parking Birmingham: Data collected from car parks in Birmingham that are operated by NCP from
Birmingham City Council. UK Open Government Licence (OGL).
https://data.birmingham.gov.uk/dataset/birmingham-parking 8. BLE RSSI dataset for Indoor localization: This dataset contains RSSIs obtained on smartphones(Sony Xperia XA1). Signals were transmitted from BLE product called iTAG. Location column denotes the position of iTAG in building's entry. 9. selfBACK: The SELFBACK dataset is a Human Activity Recognition Dataset of 9
activity classes recorded with two tri-axial accelerometers. 10. Activity Recognition system based on Multisensor data fusion (AReM): This dataset contains temporal data from a Wireless Sensor Network worn by an actor performing the activities: bending, cycling, lying down, sitting, standing, walking. 11. EMG data for gestures: These are files of raw EMG data recorded by MYO Thalmic bracelet 12. WISDM Smartphone and Smartwatch Activity and Biometrics Dataset : Contains accelerometer and gyroscope time-series sensor data collected from a smartphone and smartwatch as 51 test subjects perform 18 activities for 3 minutes each. 13. Basketball dataset: It's data collected from different volunteers that are done in a basketball practice: dribbling, pass, shoot, picking the ball, and holding the ball. 14. Occupancy Detection : Experimental data used for binary classification (room occupancy) from Temperature,Humidity,Light and CO2. Ground-truth occupancy was obtained from time stamped pictures that were taken every minute. 15. 3W dataset: The first realistic and public dataset with rare undesirable real events in oil wells. 16. Online Retail: This is a transnational data set which contains all the transactions occurring between 01/12/2010 and 09/12/2011 for a UK-based and registered non-store online retail. 17. Localization Data for Person Activity: Data contains recordings of five people performing different activities. Each person wore four sensors (tags) while performing the same scenario five times. 18. EMG Physical Action Data Set: The Physical Action Data Set includes 10 normal and 10 aggressive physical actions that measure the human activity. The data have been collected by 4 subjects using the Delsys EMG wireless apparatus. 19. Online Retail II: A real online retail transaction data set of two years. 20. ISTANBUL STOCK EXCHANGE: Data sets includes returns of Istanbul Stock Exchange with seven other international index; SP, DAX, FTSE, NIKKEI, BOVESPA, MSCE_EU, MSCI_EM from Jun 5, 2009 to Feb 22, 2011. 21. Intelligent Media Accelerometer and Gyroscope (IM-AccGyro) Dataset: The IM-AccGyro dataset is devised to benchmark techniques dealing with human activity recognition based on inertial sensors.
22. Daphnet Freezing of Gait: This dataset contains the annotated readings of 3 acceleration sensors at the hip and leg of Parkinson's disease patients that experience freezing of gait (FoG) during walking tasks.
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