1. 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.
2. 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.
3. Molecular Biology (Splice-junction Gene Sequences): Primate splice-junction gene sequences (DNA) with associated imperfect domain theory
4. 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.
5. KEGG Metabolic Relation Network (Directed): KEGG Metabolic pathways modeled as directed relation network. Variety of graphical features presented.
6. KEGG Metabolic Reaction Network (Undirected): KEGG Metabolic pathways modeled as un-directed reaction network. Variety of graphical features presented.
7. Australian Sign Language signs: This data consists of sample of Auslan (Australian Sign Language) signs. Examples of 95 signs were collected from five signers with a total of 6650 sign samples.
8. Australian Sign Language signs (High Quality): This data consists of sample of Auslan (Australian Sign Language) signs. 27 examples of each of 95 Auslan signs were captured from a native signer using high-quality position trackers
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. Connect-4: Contains connect-4 positions
11. SML2010: This dataset is collected from a monitor system mounted in a domotic house. It corresponds to approximately 40 days of monitoring data.
12. EEG Eye State: The data set consists of 14 EEG values and a value indicating the eye state.
13. 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.
14. 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'.
15. Waveform Database Generator (Version 1): CART book's waveform domains
16. Waveform Database Generator (Version 2): CART book's waveform domains
17. Adult: Predict whether income exceeds $50K/yr based on census data. Also known as "Census Income" dataset.
18. Turkiye Student Evaluation: This data set contains a total 5820 evaluation scores provided by students from Gazi University in Ankara (Turkey). There is a total of 28 course specific questions and additional 5 attributes.
19. seismic-bumps: The data describe the problem of high energy (higher than 10^4 J) seismic bumps forecasting in a coal
mine. Data come from two of longwalls located in a Polish coal mine.
20. SkillCraft1 Master Table Dataset: This data was used in Thompson et al. (2013). A list of possible game actions is discussed in Thompson, Blair, Chen, & Henrey (2013).
21. Census Income: Predict whether income exceeds $50K/yr based on census data. Also known as "Adult" dataset.
22. Chess (King-Rook vs. King-Pawn): King+Rook versus King+Pawn on a7 (usually abbreviated KRKPA7).
23. Covertype: Forest CoverType dataset
24. Image Segmentation: Image data described by high-level numeric-valued attributes, 7 classes
25. Letter Recognition: Database of character image features; try to identify the letter
26. Mushroom: From Audobon Society Field Guide; mushrooms described in terms of physical characteristics; classification: poisonous or edible
27. 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.
28. Optical Recognition of Handwritten Digits: Two versions of this database available; see folder
29. Pen-Based Recognition of Handwritten Digits: Digit database of 250 samples from 44 writers
30. Solar Flare: Each class attribute counts the number of solar flares of a certain class that occur in a 24 hour period
31. Spambase: Classifying Email as Spam or Non-Spam
32. US Census Data (1990): The USCensus1990raw data set contains a one percent sample of the Public Use Microdata Samples (PUMS) person records drawn from the full 1990 census sample.
33. Census-Income (KDD): This data set contains weighted census data extracted from the 1994 and 1995 current population surveys conducted by the U.S. Census Bureau.
34. Corel Image Features: This dataset contains image features extracted from a Corel image collection. Four sets of features are available based on the color histogram, color histogram layout, color moments, and co-occurence
35. Insurance Company Benchmark (COIL 2000): This data set used in the CoIL 2000 Challenge contains information on customers of an insurance company. The data consists of 86 variables and includes product usage data and socio-demographic data
36. Internet Usage Data: This data contains general demographic information on internet users in 1997.
37. IPUMS Census Database: This data set contains unweighted PUMS census data from the Los Angeles and Long Beach areas for the years 1970, 1980, and 1990.
38. 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
39. 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
40. Statlog (Image Segmentation): This dataset is an image segmentation database similar to a database already present in the repository (Image segmentation database) but in a slightly different form.
41. Cloud: Little Documentation
42. Poker Hand: Purpose is to predict poker hands
43. MAGIC Gamma Telescope: Data are MC generated to simulate registration of high energy gamma particles in an atmospheric Cherenkov telescope
44. Plants: Data has been extracted from the USDA plants database. It contains all plants (species and genera) in the database and the states of USA and Canada where they occur.
45. Wine Quality: Two datasets are included, related to red and white vinho verde wine samples, from the north of Portugal. The goal is to model wine quality based on physicochemical tests (see [Cortez et al., 2009], http://www3.dsi.uminho.pt/pcortez/wine/).
46. Parkinsons Telemonitoring: Oxford Parkinson's Disease Telemonitoring Dataset
47. Cardiotocography: The dataset consists of measurements of fetal heart rate (FHR) and uterine contraction (UC) features on cardiotocograms classified by expert obstetricians.
48. MiniBooNE particle identification: This dataset is taken from the MiniBooNE experiment and is used to distinguish electron neutrinos (signal) from muon neutrinos (background).
49. YearPredictionMSD: Prediction of the release year of a song from audio features. Songs are mostly western, commercial tracks ranging from 1922 to 2011, with a peak in the year 2000s.
50. Record Linkage Comparison Patterns: Element-wise comparison of records with personal data from a record linkage setting. The task is to decide from a comparison pattern whether the underlying records belong to one person.
51. Bank Marketing: The data is related with direct marketing campaigns (phone calls) of a Portuguese banking institution. The classification goal is to predict if the client will subscribe a term deposit (variable y).
52. 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.
53. QSAR biodegradation: Data set containing values for 41 attributes (molecular descriptors) used to classify 1055 chemicals into 2 classes (ready and not ready biodegradable).
54. SUSY: This is a classification problem to distinguish between a signal process which produces supersymmetric particles and a background process which does not.
55. HIGGS: This is a classification problem to distinguish between a signal process which produces Higgs bosons and a background process which does not.