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. Quality Assessment of Digital Colposcopies: This dataset explores the subjective quality assessment of digital colposcopies.
4. Parkinsons: Oxford Parkinson's Disease Detection Dataset
5. MicroMass: A dataset to explore machine learning approaches for the identification of microorganisms from mass-spectrometry data.
6. Mammographic Mass: Discrimination of benign and malignant mammographic masses based on BI-RADS attributes and the patient's age.
7. LSVT Voice Rehabilitation: 126 samples from 14 participants, 309 features. Aim: assess whether voice rehabilitation treatment lead to phonations considered 'acceptable' or 'unacceptable' (binary class classification problem).
8. Iris: Famous database; from Fisher, 1936
9. 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.
10. Haberman's Survival: Dataset contains cases from study conducted on the survival of patients who had undergone surgery for breast cancer
11. gene expression cancer RNA-Seq: This collection of data is part of the RNA-Seq (HiSeq) PANCAN data set, it is a random extraction of gene expressions of patients having different types of tumor: BRCA, KIRC, COAD, LUAD and PRAD.
12. Ecoli: This data contains protein localization sites
13. Early biomarkers of Parkinson’s disease based on natural connected speech: Predict a pattern of neurodegeneration in the dataset of speech features obtained from patients with early untreated Parkinson’s disease and patients at high risk developing Parkinson’s disease.
14. 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.
15. 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.
16. Breast Tissue: Dataset with electrical impedance measurements of freshly excised tissue samples from the breast.
17. Breast Cancer Wisconsin (Prognostic): Prognostic Wisconsin Breast Cancer Database
18. Breast Cancer Wisconsin (Original): Original Wisconsin Breast Cancer Database
19. Breast Cancer Wisconsin (Diagnostic): Diagnostic Wisconsin Breast Cancer Database
20. 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.