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