1. 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. 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 (Promoter Gene Sequences): E. Coli promoter gene sequences (DNA) with partial domain theory 4. Molecular Biology (Splice-junction Gene Sequences): Primate splice-junction gene sequences (DNA) with associated imperfect domain theory 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. Japanese Vowels: This dataset records 640 time series of 12 LPC cepstrum coefficients taken from nine male speakers. 10. 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. 11. Connect-4: Contains connect-4 positions 12. 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. 13. Libras Movement: The data set contains 15 classes of 24 instances each. Each class references to a hand movement type in LIBRAS (Portuguese
name 'LÍngua BRAsileira de Sinais', oficial brazilian signal language). 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. Chess (King-Rook vs. King-Knight): Knight Pin Chess End-Game Database Creator 16. Waveform Database Generator (Version 1): CART book's waveform domains 17. Waveform Database Generator (Version 2): CART book's waveform domains 18. Adult: Predict whether income exceeds $50K/yr based on census data. Also known as "Census Income" dataset. 19. Annealing: Steel annealing data 20. Audiology (Standardized): Standardized version of the original audiology database 21. Automobile: From 1985 Ward's Automotive Yearbook 22. Breast Cancer Wisconsin (Original): Original Wisconsin Breast Cancer Database 23. Breast Cancer Wisconsin (Prognostic): Prognostic Wisconsin Breast Cancer Database 24. Breast Cancer Wisconsin (Diagnostic): Diagnostic Wisconsin Breast Cancer Database 25. Pittsburgh Bridges: Bridges database that has original and numeric-discretized datasets 26. Census Income: Predict whether income exceeds $50K/yr based on census data. Also known as "Adult" dataset. 27. Chess (King-Rook vs. King-Pawn): King+Rook versus King+Pawn on a7 (usually abbreviated KRKPA7). 28. Credit Approval: This data concerns credit card applications; good mix of attributes 29. Covertype: Forest CoverType dataset 30. Cylinder Bands: Used in decision tree induction for mitigating process delays known as "cylinder bands" in rotogravure printing 31. Dermatology: Aim for this dataset is to determine the type of Eryhemato-Squamous Disease. 32. Echocardiogram: Data for classifying if patients will survive for at least one year after a heart attack 33. Flags: From Collins Gem Guide to Flags, 1986 34. Glass Identification: From USA Forensic Science Service; 6 types of glass; defined in terms of their oxide content (i.e. Na, Fe, K, etc) 35. Hepatitis: From G.Gong: CMU; Mostly Boolean or numeric-valued attribute types; Includes cost data (donated by Peter Turney) 36. Horse Colic: Well documented attributes; 368 instances with 28 attributes (continuous, discrete, and nominal); 30% missing values 37. Housing: Taken from StatLib library 38. Image Segmentation: Image data described by high-level numeric-valued attributes, 7 classes 39. Ionosphere: Classification of radar returns from the ionosphere 40. Letter Recognition: Database of character image features; try to identify the letter 41. Lung Cancer: Lung cancer data; no attribute definitions 42. Lymphography: This lymphography domain was obtained from the University Medical Centre, Institute of Oncology, Ljubljana, Yugoslavia. (Restricted access) 43. Meta-data: Meta-Data was used in order to give advice about which classification method is appropriate for a particular dataset (taken from results of Statlog project). 44. Mushroom: From Audobon Society Field Guide; mushrooms described in terms of physical characteristics; classification: poisonous or edible 45. 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. 46. Optical Recognition of Handwritten Digits: Two versions of this database available; see folder 47. Pen-Based Recognition of Handwritten Digits: Digit database of 250 samples from 44 writers 48. Primary Tumor: From Ljubljana Oncology Institute 49. Solar Flare: Each class attribute counts the number of solar flares of a certain class that occur in a 24 hour period 50. Soybean (Large): Michalski's famous soybean disease database 51. Soybean (Small): Michalski's famous soybean disease database 52. Spambase: Classifying Email as Spam or Non-Spam 53. SPECT Heart: Data on cardiac Single Proton Emission Computed Tomography (SPECT) images. Each patient classified into two categories: normal and abnormal. 54. SPECTF Heart: Data on cardiac Single Proton Emission Computed Tomography (SPECT) images. Each patient classified into two categories: normal and abnormal. 55. Sponge: Data on sponges; Attributes in spanish 56. Trains: 2 data formats (structured, one-instance-per-line) 57. Congressional Voting Records: 1984 United Stated Congressional Voting Records; Classify as Republican or Democrat 58. Water Treatment Plant: Multiple classes predict plant state 59. Wine: Using chemical analysis determine the origin of wines 60. Zoo: Artificial, 7 classes of animals 61. 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. 62. 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. 63. Coil 1999 Competition Data: This data set is from the 1999 Computational Intelligence and Learning (COIL) competition. The data contains measurements of river chemical concentrations and algae densities. 64. 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 65. 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 66. Internet Usage Data: This data contains general demographic information on internet users in 1997. 67. 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. 68. 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 69. Statlog (Australian Credit Approval): This file concerns credit card applications. This database exists elsewhere in the repository (Credit Screening Database) in a slightly different form 70. Statlog (German Credit Data): This dataset classifies people described by a set of attributes as good or bad credit risks. Comes in two formats (one all numeric). Also comes with a cost matrix 71. Statlog (Heart): This dataset is a heart disease database similar to a database already present in the repository (Heart Disease databases) but in a slightly different form 72. 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 73. 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. 74. Statlog (Vehicle Silhouettes): 3D objects within a 2D image by application of an ensemble of shape feature extractors to the 2D silhouettes of the objects. 75. Connectionist Bench (Sonar, Mines vs. Rocks): The task is to train a network to discriminate between sonar signals bounced off a metal cylinder and those bounced off a roughly cylindrical rock. 76. Cloud: Little Documentation 77. Poker Hand: Purpose is to predict poker hands 78. MAGIC Gamma Telescope: Data are MC generated to simulate registration of high energy gamma particles in an atmospheric Cherenkov telescope 79. Forest Fires: This is a difficult regression task, where the aim is to predict the burned area of forest fires, in the northeast region of Portugal, by using meteorological and other data (see details at: http://www.dsi.uminho.pt/~pcortez/forestfires). 80. Parkinsons: Oxford Parkinson's Disease Detection Dataset 81. 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. 82. 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. 83. 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/). 84. Parkinsons Telemonitoring: Oxford Parkinson's Disease Telemonitoring Dataset 85. Breast Tissue: Dataset with electrical impedance measurements of freshly excised tissue samples from the breast. 86. Cardiotocography: The dataset consists of measurements of fetal heart rate (FHR) and uterine contraction (UC) features on cardiotocograms classified by expert obstetricians. 87. MiniBooNE particle identification: This dataset is taken from the MiniBooNE experiment and is used to distinguish electron neutrinos (signal) from muon neutrinos (background). 88. 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. 89. 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. 90. 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). 91. 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. | 
