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. Molecular Biology (Promoter Gene Sequences): E. Coli promoter gene sequences (DNA) with partial domain theory 4. Breast Tissue: Dataset with electrical impedance measurements of freshly excised tissue samples from the breast. 5. Echocardiogram: Data for classifying if patients will survive for at least one year after a heart attack 6. Lymphography: This lymphography domain was obtained from the University Medical Centre, Institute of Oncology, Ljubljana, Yugoslavia. (Restricted access) 7. Hepatitis: From G.Gong: CMU; Mostly Boolean or numeric-valued attribute types; Includes cost data (donated by Peter Turney) 8. Parkinsons: Oxford Parkinson's Disease Detection Dataset 9. Breast Cancer Wisconsin (Prognostic): Prognostic Wisconsin Breast Cancer Database 10. Audiology (Standardized): Standardized version of the original audiology database 11. SPECT Heart: Data on cardiac Single Proton Emission Computed Tomography (SPECT) images. Each patient classified into two categories: normal and abnormal. 12. SPECTF Heart: Data on cardiac Single Proton Emission Computed Tomography (SPECT) images. Each patient classified into two categories: normal and abnormal. 13. 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 14. 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. 15. Heart Disease: 4 databases: Cleveland, Hungary, Switzerland, and the VA Long Beach 16. Soybean (Large): Michalski's famous soybean disease database 17. Primary Tumor: From Ljubljana Oncology Institute 18. Dermatology: Aim for this dataset is to determine the type of Eryhemato-Squamous Disease. 19. Horse Colic: Well documented attributes; 368 instances with 28 attributes (continuous, discrete, and nominal); 30% missing values 20. Breast Cancer Wisconsin (Diagnostic): Diagnostic Wisconsin Breast Cancer Database 21. 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. 22. Breast Cancer Wisconsin (Original): Original Wisconsin Breast Cancer Database | 
