1. 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 2. Zoo: Artificial, 7 classes of animals 3. Breast Tissue: Dataset with electrical impedance measurements of freshly excised tissue samples from the breast. 4. Pittsburgh Bridges: Bridges database that has original and numeric-discretized datasets 5. Northix: Northix is designed to be a schema matching benchmark problem for data integration of two entity relationship databases. 6. 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.
7. Japanese Credit Screening: Includes domain theory (generated by talking to Japanese domain experts); data in Lisp 8. Echocardiogram: Data for classifying if patients will survive for at least one year after a heart attack 9. Lymphography: This lymphography domain was obtained from the University Medical Centre, Institute of Oncology, Ljubljana, Yugoslavia. (Restricted access) 10. Iris: Famous database; from Fisher, 1936 11. Teaching Assistant Evaluation: The data consist of evaluations of teaching performance; scores are "low", "medium", or "high" 12. Hepatitis: From G.Gong: CMU; Mostly Boolean or numeric-valued attribute types; Includes cost data (donated by Peter Turney) 13. Hayes-Roth: Topic: human subjects study 14. Wine: Using chemical analysis determine the origin of wines 15. Flags: From Collins Gem Guide to Flags, 1986 16. Parkinsons: Oxford Parkinson's Disease Detection Dataset 17. Breast Cancer Wisconsin (Prognostic): Prognostic Wisconsin Breast Cancer Database 18. 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. 19. Mechanical Analysis: Fault diagnosis problem of electromechanical devices; also PUMPS DATA SET is newer version with domain theory and results 20. 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. 21. Glass Identification: From USA Forensic Science Service; 6 types of glass; defined in terms of their oxide content (i.e. Na, Fe, K, etc) 22. Audiology (Original): Nominal audiology dataset from Baylor 23. Audiology (Standardized): Standardized version of the original audiology database 24. 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.
25. SPECT Heart: Data on cardiac Single Proton Emission Computed Tomography (SPECT) images. Each patient classified into two categories: normal and abnormal. 26. SPECTF Heart: Data on cardiac Single Proton Emission Computed Tomography (SPECT) images. Each patient classified into two categories: normal and abnormal. 27. 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 28. University: Data in original (LISP-readable) form 29. Breast Cancer: Breast Cancer Data (Restricted Access) 30. Heart Disease: 4 databases: Cleveland, Hungary, Switzerland, and the VA Long Beach 31. Haberman's Survival: Dataset contains cases from study conducted on the survival of patients who had undergone surgery for breast cancer 32. Soybean (Large): Michalski's famous soybean disease database 33. 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). 34. 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) 35. Ecoli: This data contains protein localization sites 36. Primary Tumor: From Ljubljana Oncology Institute 37. Ionosphere: Classification of radar returns from the ionosphere 38. 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). 39. Dermatology: Aim for this dataset is to determine the type of Eryhemato-Squamous Disease. 40. Horse Colic: Well documented attributes; 368 instances with 28 attributes (continuous, discrete, and nominal); 30% missing values 41. MONK's Problems: A set of three artificial domains over the same attribute space; Used to test a wide range of induction algorithms 42. Congressional Voting Records: 1984 United Stated Congressional Voting Records; Classify as Republican or Democrat 43. 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. 44. Arrhythmia: Distinguish between the presence and absence of cardiac arrhythmia and classify it in one of the 16 groups. 45. 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 46. Musk (Version 1): The goal is to learn to predict whether new molecules will be musks or non-musks 47. Demospongiae: Marine sponges of the Demospongiae class classification domain. 48. Cylinder Bands: Used in decision tree induction for mitigating process delays known as "cylinder bands" in rotogravure printing 49. 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). 50. Low Resolution Spectrometer: From IRAS data -- NASA Ames Research Center 51. Breast Cancer Wisconsin (Diagnostic): Diagnostic Wisconsin Breast Cancer Database 52. 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. 53. Balance Scale: Balance scale weight & distance database 54. Japanese Vowels: This dataset records 640 time series of 12 LPC cepstrum coefficients taken from nine male speakers. 55. Credit Approval: This data concerns credit card applications; good mix of attributes 56. 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 57. Breast Cancer Wisconsin (Original): Original Wisconsin Breast Cancer Database 58. Blood Transfusion Service Center: Data taken from the Blood Transfusion Service Center in Hsin-Chu City in Taiwan -- this is a classification problem. 59. Pima Indians Diabetes: From National Institute of Diabetes and Digestive and Kidney Diseases; Includes cost data (donated by Peter Turney) 60. 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. 61. Annealing: Steel annealing data 62. 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. 63. 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. 64. Tic-Tac-Toe Endgame: Binary classification task on possible configurations of tic-tac-toe game 65. Mammographic Mass: Discrimination of benign and malignant mammographic masses based on BI-RADS attributes and the patient's age. 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 | 
