1. Zoo: Artificial, 7 classes of animals
2. Thyroid Disease: 10 separate databases from Garavan Institute
3. 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
4. Sponge: Data on sponges; Attributes in spanish
5. SPECTF Heart: Data on cardiac Single Proton Emission Computed Tomography (SPECT) images. Each patient classified into two categories: normal and abnormal.
6. SPECT Heart: Data on cardiac Single Proton Emission Computed Tomography (SPECT) images. Each patient classified into two categories: normal and abnormal.
7. Soybean (Small): Michalski's famous soybean disease database
8. Soybean (Large): Michalski's famous soybean disease database
9. Quadruped Mammals: The file animals.c is a data generator of structured instances representing quadruped animals
10. Primary Tumor: From Ljubljana Oncology Institute
11. 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.
12. Parkinsons Telemonitoring: Oxford Parkinson's Disease Telemonitoring Dataset
13. Parkinsons: Oxford Parkinson's Disease Detection Dataset
14. 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.
15. Mushroom: From Audobon Society Field Guide; mushrooms described in terms of physical characteristics; classification: poisonous or edible
16. Molecular Biology (Splice-junction Gene Sequences): Primate splice-junction gene sequences (DNA) with associated imperfect domain theory
17. Molecular Biology (Promoter Gene Sequences): E. Coli promoter gene sequences (DNA) with partial domain theory
18. Lymphography: This lymphography domain was obtained from the University Medical Centre, Institute of Oncology, Ljubljana, Yugoslavia. (Restricted access)
19. Lung Cancer: Lung cancer data; no attribute definitions
20. KEGG Metabolic Relation Network (Directed): KEGG Metabolic pathways modeled as directed relation network. Variety of graphical features presented.
21. KEGG Metabolic Reaction Network (Undirected): KEGG Metabolic pathways modeled as un-directed reaction network. Variety of graphical features presented.
22. 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.
23. Horse Colic: Well documented attributes; 368 instances with 28 attributes (continuous, discrete, and nominal); 30% missing values
24. Hepatitis: From G.Gong: CMU; Mostly Boolean or numeric-valued attribute types; Includes cost data (donated by Peter Turney)
25. Heart Disease: 4 databases: Cleveland, Hungary, Switzerland, and the VA Long Beach
26. 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
27. Echocardiogram: Data for classifying if patients will survive for at least one year after a heart attack
28. Diabetes: This diabetes dataset is from AIM '94
29. Dermatology: Aim for this dataset is to determine the type of Eryhemato-Squamous Disease.
30. Covertype: Forest CoverType dataset
31. Cardiotocography: The dataset consists of measurements of fetal heart rate (FHR) and uterine contraction (UC) features on cardiotocograms classified by expert obstetricians.
32. Breast Tissue: Dataset with electrical impedance measurements of freshly excised tissue samples from the breast.
33. Breast Cancer Wisconsin (Prognostic): Prognostic Wisconsin Breast Cancer Database
34. Breast Cancer Wisconsin (Original): Original Wisconsin Breast Cancer Database
35. Breast Cancer Wisconsin (Diagnostic): Diagnostic Wisconsin Breast Cancer Database
36. Audiology (Standardized): Standardized version of the original audiology database
37. 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.