Center for Machine Learning and Intelligent Systems
About  Citation Policy  Donate a Data Set  Contact


Repository Web            Google
View ALL Data Sets

Browse Through:

Default Task - Undo

Classification (68)
Regression (9)
Clustering (7)
Other (8)

Attribute Type

Categorical (13)
Numerical (39)
Mixed (14)

Data Type

Multivariate (62)
Univariate (3)
Sequential (5)
Time-Series (4)
Text (2)
Domain-Theory (3)
Other (1)

Area - Undo

Life Sciences (68)
Physical Sciences (28)
CS / Engineering (65)
Social Sciences (10)
Business (15)
Game (6)
Other (44)

# Attributes

Less than 10 (18)
10 to 100 (38)
Greater than 100 (7)

# Instances

Less than 100 (3)
100 to 1000 (39)
Greater than 1000 (24)

Format Type

Matrix (53)
Non-Matrix (15)

68 Data Sets

Table View  List View


1. Reuters RCV1 RCV2 Multilingual, Multiview Text Categorization Test collection: This test collection contains feature characteristics of documents originally written in five different languages and their translations, over a common set of 6 categories.

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

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

4. 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).

5. Tamilnadu Electricity Board Hourly Readings: This data can be effectively produced the result to fewer parameter of the Load profile can be reduced in the Database

6. Ecoli: This data contains protein localization sites

7. Iris: Famous database; from Fisher, 1936

8. sEMG for Basic Hand movements: The “sEMG for Basic Hand movements” includes 2 databases of surface electromyographic signals of 6 hand movements using Delsys' EMG System. Healthy subjects conducted six daily life grasps.

9. Cuff-Less Blood Pressure Estimation: This Data set provides preprocessed and cleaned vital signals which can be used in designing algorithms for cuff-less estimation of the blood pressure.

10. Quadruped Mammals: The file animals.c is a data generator of structured instances representing quadruped animals

11. Yeast: Predicting the Cellular Localization Sites of Proteins

12. 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.

13. Parkinsons: Oxford Parkinson's Disease Detection Dataset

14. p53 Mutants: The goal is to model mutant p53 transcriptional activity (active vs inactive) based on data extracted from biophysical simulations.

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

16. Cardiotocography: The dataset consists of measurements of fetal heart rate (FHR) and uterine contraction (UC) features on cardiotocograms classified by expert obstetricians.

17. 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.

18. 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.

19. 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.

20. 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

21. 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.

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

23. EEG Eye State: The data set consists of 14 EEG values and a value indicating the eye state.

24. 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.

25. Parkinson Speech Dataset with Multiple Types of Sound Recordings: The training data belongs to 20 Parkinson's Disease (PD) patients and 20 healthy subjects. From all subjects, multiple types of sound recordings (26) are taken.

26. Diabetic Retinopathy Debrecen Data Set: This dataset contains features extracted from the Messidor image set to predict whether an image contains signs of diabetic retinopathy or not.

27. Pima Indians Diabetes: From National Institute of Diabetes and Digestive and Kidney Diseases; Includes cost data (donated by Peter Turney)

28. 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.

29. KEGG Metabolic Relation Network (Directed): KEGG Metabolic pathways modeled as directed relation network. Variety of graphical features presented.

30. KEGG Metabolic Reaction Network (Undirected): KEGG Metabolic pathways modeled as un-directed reaction network. Variety of graphical features presented.

31. 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.

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

33. Diabetes 130-US hospitals for years 1999-2008: This data has been prepared to analyze factors related to readmission as well as other outcomes pertaining to patients with diabetes.

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

35. Lung Cancer: Lung cancer data; no attribute definitions

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

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

38. 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.

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

40. Thyroid Disease: 10 separate databases from Garavan Institute

41. 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

42. Abalone: Predict the age of abalone from physical measurements

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

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

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

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

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

48. Contraceptive Method Choice: Dataset is a subset of the 1987 National Indonesia Contraceptive Prevalence Survey.

49. Covertype: Forest CoverType dataset

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

51. Post-Operative Patient: Dataset of patient features

52. Zoo: Artificial, 7 classes of animals

53. 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.

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

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

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

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

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

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

60. Molecular Biology (Splice-junction Gene Sequences): Primate splice-junction gene sequences (DNA) with associated imperfect domain theory

61. Mushroom: From Audobon Society Field Guide; mushrooms described in terms of physical characteristics; classification: poisonous or edible

62. HIV-1 protease cleavage: The data contains lists of octamers (8 amino acids) and a flag (-1 or 1) depending on whether HIV-1 protease will cleave in the central position (between amino acids 4 and 5).

63. Primary Tumor: From Ljubljana Oncology Institute

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

65. Soybean (Small): Michalski's famous soybean disease database

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

67. Wilt: High-resolution Remote Sensing data set (Quickbird). Small number of training samples of diseased trees, large number for other land cover. Testing data set from stratified random sample of image.

68. 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.


Supported By:

 In Collaboration With:

About  ||  Citation Policy  ||  Donation Policy  ||  Contact  ||  CML