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