1. Audiology (Original): Nominal audiology dataset from Baylor
2. Molecular Biology (Protein Secondary Structure): From CMU connectionist bench repository; Classifies secondary structure of certain globular proteins
3. Demospongiae: Marine sponges of the Demospongiae class classification domain.
4. Haberman's Survival: Dataset contains cases from study conducted on the survival of patients who had undergone surgery for breast cancer
5. Iris: Famous database; from Fisher, 1936
6. EEG Database: This data arises from a large study to examine EEG correlates of genetic predisposition to alcoholism. It contains measurements from 64 electrodes placed on the scalp sampled at 256 Hz
7. Mammographic Mass: Discrimination of benign and malignant mammographic masses based on BI-RADS attributes and the patient's age.
8. 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.
9. Liver Disorders: BUPA Medical Research Ltd. database donated by Richard S. Forsyth
10. 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.
11. Ecoli: This data contains protein localization sites
12. Pima Indians Diabetes: From National Institute of Diabetes and Digestive and Kidney Diseases; Includes cost data (donated by Peter Turney)
13. Breast Cancer: Breast Cancer Data (Restricted Access)
14. 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.
15. Breast Cancer Wisconsin (Original): Original Wisconsin Breast Cancer Database
16. Breast Tissue: Dataset with electrical impedance measurements of freshly excised tissue samples from the breast.
17. 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.
18. 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
19. Echocardiogram: Data for classifying if patients will survive for at least one year after a heart attack
20. 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
21. Primary Tumor: From Ljubljana Oncology Institute
22. Zoo: Artificial, 7 classes of animals
23. Lymphography: This lymphography domain was obtained from the University Medical Centre, Institute of Oncology, Ljubljana, Yugoslavia. (Restricted access)
24. Hepatitis: From G.Gong: CMU; Mostly Boolean or numeric-valued attribute types; Includes cost data (donated by Peter Turney)
25. SPECT Heart: Data on cardiac Single Proton Emission Computed Tomography (SPECT) images. Each patient classified into two categories: normal and abnormal.
26. Parkinsons: Oxford Parkinson's Disease Detection Dataset
27. Horse Colic: Well documented attributes; 368 instances with 28 attributes (continuous, discrete, and nominal); 30% missing values
28. Breast Cancer Wisconsin (Diagnostic): Diagnostic Wisconsin Breast Cancer Database
29. Dermatology: Aim for this dataset is to determine the type of Eryhemato-Squamous Disease.
30. Breast Cancer Wisconsin (Prognostic): Prognostic Wisconsin Breast Cancer Database
31. Soybean (Large): Michalski's famous soybean disease database
32. 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.
33. SPECTF Heart: Data on cardiac Single Proton Emission Computed Tomography (SPECT) images. Each patient classified into two categories: normal and abnormal.
34. Molecular Biology (Promoter Gene Sequences): E. Coli promoter gene sequences (DNA) with partial domain theory
35. Audiology (Standardized): Standardized version of the original audiology database
36. Heart Disease: 4 databases: Cleveland, Hungary, Switzerland, and the VA Long Beach
37. Arrhythmia: Distinguish between the presence and absence of cardiac arrhythmia and classify it in one of the 16 groups.
38. 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.