1. Arrhythmia: Distinguish between the presence and absence of cardiac arrhythmia and classify it in one of the 16 groups.
2. Audiology (Standardized): Standardized version of the original audiology database
3. Breast Cancer: Breast Cancer Data (Restricted Access)
4. Breast Cancer Wisconsin (Original): Original Wisconsin Breast Cancer Database
5. Breast Cancer Wisconsin (Diagnostic): Diagnostic Wisconsin Breast Cancer Database
6. Dermatology: Aim for this dataset is to determine the type of Eryhemato-Squamous Disease.
7. Echocardiogram: Data for classifying if patients will survive for at least one year after a heart attack
8. Ecoli: This data contains protein localization sites
9. Haberman's Survival: Dataset contains cases from study conducted on the survival of patients who had undergone surgery for breast cancer
10. Hepatitis: From G.Gong: CMU; Mostly Boolean or numeric-valued attribute types; Includes cost data (donated by Peter Turney)
11. Horse Colic: Well documented attributes; 368 instances with 28 attributes (continuous, discrete, and nominal); 30% missing values
12. Iris: Famous database; from Fisher, 1936
13. Lymphography: This lymphography domain was obtained from the University Medical Centre, Institute of Oncology, Ljubljana, Yugoslavia. (Restricted access)
14. Pima Indians Diabetes: From National Institute of Diabetes and Digestive and Kidney Diseases; Includes cost data (donated by Peter Turney)
15. Primary Tumor: From Ljubljana Oncology Institute
16. Soybean (Large): Michalski's famous soybean disease database
17. SPECT Heart: Data on cardiac Single Proton Emission Computed Tomography (SPECT) images. Each patient classified into two categories: normal and abnormal.
18. SPECTF Heart: Data on cardiac Single Proton Emission Computed Tomography (SPECT) images. Each patient classified into two categories: normal and abnormal.
19. Zoo: Artificial, 7 classes of animals
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. Mammographic Mass: Discrimination of benign and malignant mammographic masses based on BI-RADS attributes and the patient's age.
22. 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.
23. Parkinsons: Oxford Parkinson's Disease Detection Dataset
24. 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.
25. Breast Tissue: Dataset with electrical impedance measurements of freshly excised tissue samples from the breast.
26. 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.
27. MicroMass: A dataset to explore machine learning approaches for the identification of microorganisms from mass-spectrometry data.
28. 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.
29. Breast Cancer Wisconsin (Prognostic): Prognostic Wisconsin Breast Cancer Database