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49 Data Sets

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1. 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.

2. 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.

3. Arrhythmia: Distinguish between the presence and absence of cardiac arrhythmia and classify it in one of the 16 groups.

4. Audiology (Original): Nominal audiology dataset from Baylor

5. Audiology (Standardized): Standardized version of the original audiology database

6. Autistic Spectrum Disorder Screening Data for Adolescent : Autistic Spectrum Disorder Screening Data for Adolescent. This dataset is related to classification and predictive tasks.

7. Autistic Spectrum Disorder Screening Data for Children : Children screening data for autism suitable for classification and predictive tasks

8. Breast Cancer: Breast Cancer Data (Restricted Access)

9. Breast Cancer Coimbra: Clinical features were observed or measured for 64 patients with breast cancer and 52 healthy controls.

10. Breast Cancer Wisconsin (Diagnostic): Diagnostic Wisconsin Breast Cancer Database

11. Breast Cancer Wisconsin (Original): Original Wisconsin Breast Cancer Database

12. Breast Cancer Wisconsin (Prognostic): Prognostic Wisconsin Breast Cancer Database

13. Breast Tissue: Dataset with electrical impedance measurements of freshly excised tissue samples from the breast.

14. 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.

15. 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.

16. Demospongiae: Marine sponges of the Demospongiae class classification domain.

17. Dermatology: Aim for this dataset is to determine the type of Eryhemato-Squamous Disease.

18. 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.

19. Echocardiogram: Data for classifying if patients will survive for at least one year after a heart attack

20. Ecoli: This data contains protein localization sites

21. extention of Z-Alizadeh sani dataset: It was collected for CAD diagnosis.

22. 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

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. 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.

25. Haberman's Survival: Dataset contains cases from study conducted on the survival of patients who had undergone surgery for breast cancer

26. 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.

27. Heart Disease: 4 databases: Cleveland, Hungary, Switzerland, and the VA Long Beach

28. Hepatitis: From G.Gong: CMU; Mostly Boolean or numeric-valued attribute types; Includes cost data (donated by Peter Turney)

29. Horse Colic: Well documented attributes; 368 instances with 28 attributes (continuous, discrete, and nominal); 30% missing values

30. 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.

31. Iris: Famous database; from Fisher, 1936

32. 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).

33. Lymphography: This lymphography domain was obtained from the University Medical Centre, Institute of Oncology, Ljubljana, Yugoslavia. (Restricted access)

34. Mammographic Mass: Discrimination of benign and malignant mammographic masses based on BI-RADS attributes and the patient's age.

35. MicroMass: A dataset to explore machine learning approaches for the identification of microorganisms from mass-spectrometry data.

36. Molecular Biology (Promoter Gene Sequences): E. Coli promoter gene sequences (DNA) with partial domain theory

37. Molecular Biology (Protein Secondary Structure): From CMU connectionist bench repository; Classifies secondary structure of certain globular proteins

38. Parkinsons: Oxford Parkinson's Disease Detection Dataset

39. Primary Tumor: From Ljubljana Oncology Institute

40. Quality Assessment of Digital Colposcopies: This dataset explores the subjective quality assessment of digital colposcopies.

41. 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.

42. Somerville Happiness Survey: A data extract of a non-federal dataset posted here https://catalog.data.gov/dataset/somerville-happiness-survey-responses-2011-2013-2015

43. Soybean (Large): Michalski's famous soybean disease database

44. SPECT Heart: Data on cardiac Single Proton Emission Computed Tomography (SPECT) images. Each patient classified into two categories: normal and abnormal.

45. SPECTF Heart: Data on cardiac Single Proton Emission Computed Tomography (SPECT) images. Each patient classified into two categories: normal and abnormal.

46. 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

47. 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.

48. Z-Alizadeh Sani: It was collected for CAD diagnosis.

49. Zoo: Artificial, 7 classes of animals


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