1. SPECTF Heart: Data on cardiac Single Proton Emission Computed Tomography (SPECT) images. Each patient classified into two categories: normal and abnormal. 2. 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. 3. Pima Indians Diabetes: From National Institute of Diabetes and Digestive and Kidney Diseases; Includes cost data (donated by Peter Turney) 4. Parkinsons: Oxford Parkinson's Disease Detection Dataset 5. Mammographic Mass: Discrimination of benign and malignant mammographic masses based on BI-RADS attributes and the patient's age. 6. Iris: Famous database; from Fisher, 1936 7. Haberman's Survival: Dataset contains cases from study conducted on the survival of patients who had undergone surgery for breast cancer 8. Ecoli: This data contains protein localization sites 9. 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.
10. Breast Tissue: Dataset with electrical impedance measurements of freshly excised tissue samples from the breast. 11. Breast Cancer Wisconsin (Prognostic): Prognostic Wisconsin Breast Cancer Database 12. Breast Cancer Wisconsin (Original): Original Wisconsin Breast Cancer Database 13. Breast Cancer Wisconsin (Diagnostic): Diagnostic Wisconsin Breast Cancer Database 14. 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. | 
