1. Audiology (Standardized): Standardized version of the original audiology database
2. Lymphography: This lymphography domain was obtained from the University Medical Centre, Institute of Oncology, Ljubljana, Yugoslavia. (Restricted access)
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. Mushroom: From Audobon Society Field Guide; mushrooms described in terms of physical characteristics; classification: poisonous or edible
6. Primary Tumor: From Ljubljana Oncology Institute
7. Soybean (Large): Michalski's famous soybean disease database
8. Soybean (Small): Michalski's famous soybean disease database
9. SPECT Heart: Data on cardiac Single Proton Emission Computed Tomography (SPECT) images. Each patient classified into two categories: normal and abnormal.
10. 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.
11. Covertype: Forest CoverType dataset
12. Dermatology: Aim for this dataset is to determine the type of Eryhemato-Squamous Disease.
13. Diabetes: This diabetes dataset is from AIM '94
14. Sponge: Data on sponges; Attributes in spanish
15. Zoo: Artificial, 7 classes of animals
16. Echocardiogram: Data for classifying if patients will survive for at least one year after a heart attack
17. Heart Disease: 4 databases: Cleveland, Hungary, Switzerland, and the VA Long Beach
18. Hepatitis: From G.Gong: CMU; Mostly Boolean or numeric-valued attribute types; Includes cost data (donated by Peter Turney)
19. Horse Colic: Well documented attributes; 368 instances with 28 attributes (continuous, discrete, and nominal); 30% missing values
20. Thyroid Disease: 10 separate databases from Garavan Institute
21. 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
22. Breast Cancer Wisconsin (Original): Original Wisconsin Breast Cancer Database
23. Lung Cancer: Lung cancer data; no attribute definitions
24. SPECTF Heart: Data on cardiac Single Proton Emission Computed Tomography (SPECT) images. Each patient classified into two categories: normal and abnormal.
25. Abscisic Acid Signaling Network: The objective is to determine the set of boolean rules that describe the interactions of the nodes within this plant signaling network. The dataset includes 300 separate boolean pseudodynamic simulations using an asynchronous update scheme.
26. Parkinsons Telemonitoring: Oxford Parkinson's Disease Telemonitoring Dataset
27. KEGG Metabolic Relation Network (Directed): KEGG Metabolic pathways modeled as directed relation network. Variety of graphical features presented.
28. KEGG Metabolic Reaction Network (Undirected): KEGG Metabolic pathways modeled as un-directed reaction network. Variety of graphical features presented.
29. 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.
30. Breast Cancer Wisconsin (Prognostic): Prognostic Wisconsin Breast Cancer Database
31. Breast Cancer Wisconsin (Diagnostic): Diagnostic Wisconsin Breast Cancer Database
32. Quadruped Mammals: The file animals.c is a data generator of structured instances representing quadruped animals
33. Parkinsons: Oxford Parkinson's Disease Detection Dataset
34. Breast Tissue: Dataset with electrical impedance measurements of freshly excised tissue samples from the breast.
35. Cardiotocography: The dataset consists of measurements of fetal heart rate (FHR) and uterine contraction (UC) features on cardiotocograms classified by expert obstetricians.
36. One-hundred plant species leaves data set: Sixteen samples of leaf each of one-hundred plant species. For each sample, a shape descriptor, fine scale margin and texture histogram are given.
37. 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