1. Airfoil Self-Noise: NASA data set, obtained from a series of aerodynamic and acoustic tests of two and three-dimensional airfoil blade sections conducted in an anechoic wind tunnel.
2. Amazon Commerce reviews set: The dataset is used for authorship identification in online Writeprint which is a new research field of pattern recognition.
3. Beijing Multi-Site Air-Quality Data: This hourly data set considers 6 main air pollutants and 6 relevant meteorological variables at multiple sites in Beijing.
4. Beijing PM2.5 Data: This hourly data set contains the PM2.5 data of US Embassy in Beijing. Meanwhile, meteorological data from Beijing Capital International Airport are also included.
5. Bias correction of numerical prediction model temperature forecast: It contains fourteen numerical weather prediction (NWP)'s meteorological forecast data, two in-situ observations, and five geographical auxiliary variables over Seoul, South Korea in the summer.
6. Cloud: Little Documentation
7. Concrete Compressive Strength: Concrete is the most important material in civil engineering. The concrete compressive strength is a highly nonlinear function of age and ingredients.
8. El Nino: The data set contains oceanographic and surface meteorological readings taken from a series of buoys positioned throughout the equatorial Pacific.
9. Electrical Grid Stability Simulated Data : The local stability analysis of the 4-node star system (electricity producer is in the center) implementing Decentral Smart Grid Control concept.
10. 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.
11. Greenhouse Gas Observing Network: Design an observing network to monitor emissions of a greenhouse gas (GHG) in California given time series of synthetic observations and tracers from weather model simulations.
12. HEPMASS: The search for exotic particles requires sorting through a large number of collisions to find the events of interest. This data set challenges one to detect a new particle of unknown mass.
13. HIGGS: This is a classification problem to distinguish between a signal process which produces Higgs bosons and a background process which does not.
14. HTRU2: Pulsar candidates collected during the HTRU survey. Pulsars are a type of star, of considerable scientific interest. Candidates must be classified in to pulsar and non-pulsar classes to aid discovery.
15. Individual household electric power consumption: Measurements of electric power consumption in one household with a one-minute sampling rate over a period of almost 4 years. Different electrical quantities and some sub-metering values are available.
16. MAGIC Gamma Telescope: Data are MC generated to simulate registration of high energy gamma particles in an atmospheric Cherenkov telescope
17. MiniBooNE particle identification: This dataset is taken from the MiniBooNE experiment and is used to distinguish electron neutrinos (signal) from muon neutrinos (background).
18. Musk (Version 2): The goal is to learn to predict whether new molecules will be musks or non-musks
19. Ozone Level Detection: Two ground ozone level data sets are included in this collection. One is the eight hour peak set (eighthr.data), the other is the one hour peak set (onehr.data). Those data were collected from 1998 to 2004 at the Houston, Galveston and Brazoria area.
20. PM2.5 Data of Five Chinese Cities: This hourly data set contains the PM2.5 data in Beijing, Shanghai, Guangzhou, Chengdu and Shenyang. Meanwhile, meteorological data for each city are also included.
21. Statlog (Landsat Satellite): Multi-spectral values of pixels in 3x3 neighbourhoods in a satellite image, and the classification associated with the central pixel in each neighbourhood
22. Statlog (Shuttle): The shuttle dataset contains 9 attributes all of which are numerical. Approximately 80% of the data belongs to class 1
23. Steel Plates Faults: A dataset of steel plates’ faults, classified into 7 different types.
The goal was to train machine learning for automatic pattern recognition.
24. Superconductivty Data: Two file s contain data on 21263 superconductors and their relevant features.
25. SUSY: This is a classification problem to distinguish between a signal process which produces supersymmetric particles and a background process which does not.
26. Vicon 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 10 subjects using the Vicon 3D tracker.
27. Waveform Database Generator (Version 1): CART book's waveform domains
28. Waveform Database Generator (Version 2): CART book's waveform domains
29. Weight Lifting Exercises monitored with Inertial Measurement Units: Six young health subjects were asked to perform 5 variations of the biceps curl weight lifting exercise. One of the variations is the one predicted by the health professional.