1. Zoo: Artificial, 7 classes of animals
2. Thoracic Surgery Data: The data is dedicated to classification problem related to the post-operative life expectancy in the lung cancer patients: class 1 - death within one year after surgery, class 2 - survival.
3. 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
4. SPECTF Heart: Data on cardiac Single Proton Emission Computed Tomography (SPECT) images. Each patient classified into two categories: normal and abnormal.
5. SPECT Heart: Data on cardiac Single Proton Emission Computed Tomography (SPECT) images. Each patient classified into two categories: normal and abnormal.
6. Soybean (Large): Michalski's famous soybean disease database
7. Risk Factor prediction of Chronic Kidney Disease: Chronic kidney disease (CKD) is an increasing medical issue that declines the productivity of renal capacities and subsequently damages the kidneys.
8. Refractive errors: Effect of life style and genetic on eye refractive errors.
9. Quality Assessment of Digital Colposcopies: This dataset explores the subjective quality assessment of digital colposcopies.
10. QSAR Bioconcentration classes dataset: Dataset of manually-curated Bioconcentration factor (BCF, fish) and mechanistic classes for QSAR modeling.
11. Primary Tumor: From Ljubljana Oncology Institute
12. Parkinsons: Oxford Parkinson's Disease Detection Dataset
13. Parkinson Dataset with replicated acoustic features : Contains acoustic features extracted from 3 voice recording replications of the sustained /a/ phonation for each one of the 80 subjects (40 of them with Parkinson's Disease).
14. Nasarian CAD Dataset: This dataset comprises records of 150 subjects (all male employees in Iran have visited the Abadan Occupational (Industrial) Medicine Clinic) and 52 features.
15. Lymphography: This lymphography domain was obtained from the University Medical Centre, Institute of Oncology, Ljubljana, Yugoslavia. (Restricted access)
16. 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.
17. Horse Colic: Well documented attributes; 368 instances with 28 attributes (continuous, discrete, and nominal); 30% missing values
18. Hepatitis: From G.Gong: CMU; Mostly Boolean or numeric-valued attribute types; Includes cost data (donated by Peter Turney)
19. Heart failure clinical records: This dataset contains the medical records of 299 patients who had heart failure, collected during their follow-up period, where each patient profile has 13 clinical features.
20. Heart Disease: 4 databases: Cleveland, Hungary, Switzerland, and the VA Long Beach
21. HCV data: The data set contains laboratory values of blood donors and Hepatitis C patients and demographic values like age.
22. HCC Survival: Hepatocellular Carcinoma dataset (HCC dataset) was collected at a University Hospital in Portugal. It contains real clinical data of 165 patients diagnosed with HCC.
23. Forest type mapping: Multi-temporal remote sensing data of a forested area in Japan. The goal is to map different forest types using spectral data.
24. 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
25. Echocardiogram: Data for classifying if patients will survive for at least one year after a heart attack
26. Early biomarkers of Parkinsonís disease based on natural connected speech: Predict a pattern of neurodegeneration in the dataset of speech features obtained from patients with early untreated Parkinson‚Äôs disease and patients at high risk developing Parkinson‚Äôs disease.
27. Divorce Predictors data set: Participants completed the ‚ÄúPersonal Information Form‚ÄĚ and ‚ÄúDivorce Predictors Scale‚ÄĚ.
28. Divorce Predictors data set: Participants completed the Personal Information Form and Divorce Predictors Scale.
29. Dermatology: Aim for this dataset is to determine the type of Eryhemato-Squamous Disease.
30. Cervical cancer (Risk Factors): This dataset focuses on the prediction of indicators/diagnosis of cervical cancer. The features cover demographic information, habits, and historic medical records.
31. Breast Tissue: Dataset with electrical impedance measurements of freshly excised tissue samples from the breast.
32. Breast Cancer Wisconsin (Prognostic): Prognostic Wisconsin Breast Cancer Database
33. Breast Cancer Wisconsin (Original): Original Wisconsin Breast Cancer Database
34. Breast Cancer Wisconsin (Diagnostic): Diagnostic Wisconsin Breast Cancer Database
35. Breast Cancer Coimbra: Clinical features were observed or measured for 64 patients with breast cancer and 52 healthy controls.
36. Bone marrow transplant: children: The data set describes pediatric patients with several hematologic diseases, who were subject to the unmanipulated allogeneic unrelated donor hematopoietic stem cell transplantation.
37. Autistic Spectrum Disorder Screening Data for Children : Children screening data for autism suitable for classification and predictive tasks
38. Autistic Spectrum Disorder Screening Data for Adolescent : Autistic Spectrum Disorder Screening Data for Adolescent. This dataset is related to classification and predictive tasks.
39. Audiology (Standardized): Standardized version of the original audiology database
40. Amphibians: The dataset is a multilabel classification problem. The goal is to predict the presence of amphibians species near the water reservoirs based on features obtained from GIS systems and satellite images
41. Algerian Forest Fires Dataset : The dataset includes 244 instances that regroup a data of two regions of Algeria.
42. 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.