1. Demospongiae: Marine sponges of the Demospongiae class classification domain. 2. PubChem Bioassay Data: These highly imbalanced bioassay datasets are from the differing types of screening that can be performed using HTS technology. 21 datasets were created from 12 bioassays. 3. Haberman's Survival: Dataset contains cases from study conducted on the survival of patients who had undergone surgery for breast cancer 4. Iris: Famous database; from Fisher, 1936 5. Mammographic Mass: Discrimination of benign and malignant mammographic masses based on BI-RADS attributes and the patient's age. 6. 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. 7. Ecoli: This data contains protein localization sites 8. Pima Indians Diabetes: From National Institute of Diabetes and Digestive and Kidney Diseases; Includes cost data (donated by Peter Turney) 9. Yeast: Predicting the Cellular Localization Sites of Proteins 10. Localization Data for Person Activity: Data contains recordings of five people performing different activities. Each person wore four sensors (tags) while performing the same scenario five times. 11. 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.
12. Breast Cancer Wisconsin (Original): Original Wisconsin Breast Cancer Database 13. Breast Tissue: Dataset with electrical impedance measurements of freshly excised tissue samples from the breast. 14. 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. 15. 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 16. Parkinsons: Oxford Parkinson's Disease Detection Dataset 17. Cardiotocography: The dataset consists of measurements of fetal heart rate (FHR) and uterine contraction (UC) features on cardiotocograms classified by expert obstetricians. 18. KEGG Metabolic Relation Network (Directed): KEGG Metabolic pathways modeled as directed relation network. Variety of graphical features presented. 19. KEGG Metabolic Reaction Network (Undirected): KEGG Metabolic pathways modeled as un-directed reaction network. Variety of graphical features presented. 20. Breast Cancer Wisconsin (Diagnostic): Diagnostic Wisconsin Breast Cancer Database 21. Breast Cancer Wisconsin (Prognostic): Prognostic Wisconsin Breast Cancer Database 22. SPECTF Heart: Data on cardiac Single Proton Emission Computed Tomography (SPECT) images. Each patient classified into two categories: normal and abnormal. 23. Lung Cancer: Lung cancer data; no attribute definitions 24. 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. 25. Quadruped Mammals: The file animals.c is a data generator of structured instances representing quadruped animals 26. p53 Mutants: The goal is to model mutant p53 transcriptional activity (active vs inactive) based on data extracted from biophysical simulations.
27. 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. 28. Dorothea: DOROTHEA is a drug discovery dataset. Chemical compounds represented by structural molecular features must be classified as active (binding to thrombin) or inactive. This is one of 5 datasets of the NIPS 2003 feature selection challenge. | 
