1. Acute Inflammations: The data was created by a medical expert as a data set to test the expert system,
which will perform the presumptive diagnosis of two diseases of the urinary system.
2. Annealing: Steel annealing data 3. Arcene: ARCENE's task is to distinguish cancer versus normal patterns from mass-spectrometric data. This is a two-class classification problem with continuous input variables. This dataset is one of 5 datasets of the NIPS 2003 feature selection challenge. 4. Arrhythmia: Distinguish between the presence and absence of cardiac arrhythmia and classify it in one of the 16 groups. 5. Audiology (Original): Nominal audiology dataset from Baylor 6. Audiology (Standardized): Standardized version of the original audiology database 7. Badges: Badges labeled with a "+" or "-" as a function of a person's name 8. Balance Scale: Balance scale weight & distance database 9. Blood Transfusion Service Center: Data taken from the Blood Transfusion Service Center in Hsin-Chu City in Taiwan -- this is a classification problem. 10. Breast Cancer: Breast Cancer Data (Restricted Access) 11. Breast Cancer Wisconsin (Diagnostic): Diagnostic Wisconsin Breast Cancer Database 12. Breast Cancer Wisconsin (Original): Original Wisconsin Breast Cancer Database 13. Breast Cancer Wisconsin (Prognostic): Prognostic Wisconsin Breast Cancer Database 14. Breast Tissue: Dataset with electrical impedance measurements of freshly excised tissue samples from the breast. 15. CMU Face Images: This data consists of 640 black and white face images of people taken with varying pose (straight, left, right, up), expression (neutral, happy, sad, angry), eyes (wearing sunglasses or not), and size 16. Congressional Voting Records: 1984 United Stated Congressional Voting Records; Classify as Republican or Democrat 17. 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. 18. Connectionist Bench (Vowel Recognition - Deterding Data): Speaker independent recognition of the eleven steady state vowels of British English using a specified training set of lpc derived log area ratios. 19. Credit Approval: This data concerns credit card applications; good mix of attributes 20. Cylinder Bands: Used in decision tree induction for mitigating process delays known as "cylinder bands" in rotogravure printing 21. 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.
22. Demospongiae: Marine sponges of the Demospongiae class classification domain. 23. Dermatology: Aim for this dataset is to determine the type of Eryhemato-Squamous Disease. 24. Echocardiogram: Data for classifying if patients will survive for at least one year after a heart attack 25. Ecoli: This data contains protein localization sites 26. 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. 27. Fertility: 100 volunteers provide a semen sample analyzed according to the WHO 2010 criteria. Sperm concentration are related to socio-demographic data, environmental factors, health status, and life habits 28. Flags: From Collins Gem Guide to Flags, 1986 29. Glass Identification: From USA Forensic Science Service; 6 types of glass; defined in terms of their oxide content (i.e. Na, Fe, K, etc) 30. Haberman's Survival: Dataset contains cases from study conducted on the survival of patients who had undergone surgery for breast cancer 31. Hayes-Roth: Topic: human subjects study 32. Heart Disease: 4 databases: Cleveland, Hungary, Switzerland, and the VA Long Beach 33. Hepatitis: From G.Gong: CMU; Mostly Boolean or numeric-valued attribute types; Includes cost data (donated by Peter Turney) 34. Hill-Valley: Each record represents 100 points on a two-dimensional graph. When plotted in order (from 1 through 100) as the Y co-ordinate, the points will create either a Hill (a “bump” in the terrain) or a Valley (a “dip” in the terrain). 35. Horse Colic: Well documented attributes; 368 instances with 28 attributes (continuous, discrete, and nominal); 30% missing values 36. ILPD (Indian Liver Patient Dataset): This data set contains 10 variables that are age, gender, total Bilirubin, direct Bilirubin, total proteins, albumin, A/G ratio, SGPT, SGOT and Alkphos. 37. Ionosphere: Classification of radar returns from the ionosphere 38. Iris: Famous database; from Fisher, 1936 39. 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. 40. Japanese Credit Screening: Includes domain theory (generated by talking to Japanese domain experts); data in Lisp 41. Japanese Vowels: This dataset records 640 time series of 12 LPC cepstrum coefficients taken from nine male speakers. 42. 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). 43. Low Resolution Spectrometer: From IRAS data -- NASA Ames Research Center 44. Lymphography: This lymphography domain was obtained from the University Medical Centre, Institute of Oncology, Ljubljana, Yugoslavia. (Restricted access) 45. Mammographic Mass: Discrimination of benign and malignant mammographic masses based on BI-RADS attributes and the patient's age. 46. Mechanical Analysis: Fault diagnosis problem of electromechanical devices; also PUMPS DATA SET is newer version with domain theory and results 47. 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). 48. Molecular Biology (Promoter Gene Sequences): E. Coli promoter gene sequences (DNA) with partial domain theory 49. Molecular Biology (Protein Secondary Structure): From CMU connectionist bench repository; Classifies secondary structure of certain globular proteins 50. MONK's Problems: A set of three artificial domains over the same attribute space; Used to test a wide range of induction algorithms 51. Musk (Version 1): The goal is to learn to predict whether new molecules will be musks or non-musks 52. Northix: Northix is designed to be a schema matching benchmark problem for data integration of two entity relationship databases. 53. Parkinsons: Oxford Parkinson's Disease Detection Dataset 54. 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. 55. Pima Indians Diabetes: From National Institute of Diabetes and Digestive and Kidney Diseases; Includes cost data (donated by Peter Turney) 56. Pittsburgh Bridges: Bridges database that has original and numeric-discretized datasets 57. 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. 58. Primary Tumor: From Ljubljana Oncology Institute 59. Reuters Transcribed Subset: This dataset is created by reading out 200 files from the 10 largest Reuters
classes and using an Automatic Speech Recognition system to create
corresponding transcriptions. 60. Robot Execution Failures: This dataset contains force and torque measurements on a robot after failure detection. Each failure is characterized by 15 force/torque samples collected at regular time intervals 61. seeds: Measurements of geometrical properties of kernels belonging to three different varieties of wheat. A soft X-ray technique and GRAINS package were used to construct all seven, real-valued attributes. 62. Soybean (Large): Michalski's famous soybean disease database 63. SPECT Heart: Data on cardiac Single Proton Emission Computed Tomography (SPECT) images. Each patient classified into two categories: normal and abnormal. 64. SPECTF Heart: Data on cardiac Single Proton Emission Computed Tomography (SPECT) images. Each patient classified into two categories: normal and abnormal. 65. 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 66. 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 67. 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 68. 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. 69. Synthetic Control Chart Time Series: This data consists of synthetically generated control charts. 70. Syskill and Webert Web Page Ratings: This database contains HTML source of web pages plus the ratings of a single user on these web pages. Web pages are on four seperate subjects (Bands- recording artists; Goats; Sheep; and BioMedical) 71. Teaching Assistant Evaluation: The data consist of evaluations of teaching performance; scores are "low", "medium", or "high" 72. Tic-Tac-Toe Endgame: Binary classification task on possible configurations of tic-tac-toe game 73. University: Data in original (LISP-readable) form 74. Vertebral Column: Data set containing values for six biomechanical features used to classify orthopaedic patients into 3 classes (normal, disk hernia or spondilolysthesis) or 2 classes (normal or abnormal). 75. Wine: Using chemical analysis determine the origin of wines 76. Zoo: Artificial, 7 classes of animals | 
