1. Breast Cancer Wisconsin (Prognostic): Prognostic Wisconsin Breast Cancer Database
2. Breast Cancer Wisconsin (Diagnostic): Diagnostic Wisconsin Breast Cancer Database
3. Ecoli: This data contains protein localization sites
4. Glass Identification: From USA Forensic Science Service; 6 types of glass; defined in terms of their oxide content (i.e. Na, Fe, K, etc)
5. Image Segmentation: Image data described by high-level numeric-valued attributes, 7 classes
6. Iris: Famous database; from Fisher, 1936
7. ISOLET: Goal: Predict which letter-name was spoken--a simple classification task.
8. Quadruped Mammals: The file animals.c is a data generator of structured instances representing quadruped animals
9. Waveform Database Generator (Version 1): CART book's waveform domains
10. Waveform Database Generator (Version 2): CART book's waveform domains
11. Yeast: Predicting the Cellular Localization Sites of Proteins
12. Australian Sign Language signs (High Quality): This data consists of sample of Auslan (Australian Sign Language) signs. 27 examples of each of 95 Auslan signs were captured from a native signer using high-quality position trackers
13. Japanese Vowels: This dataset records 640 time series of 12 LPC cepstrum coefficients taken from nine male speakers.
14. Statlog (Image Segmentation): This dataset is an image segmentation database similar to a database already present in the repository (Image segmentation database) but in a slightly different form.
15. Connectionist Bench (Sonar, Mines vs. Rocks): The task is to train a network to discriminate between sonar signals bounced off a metal cylinder and those bounced off a roughly cylindrical rock.
16. MAGIC Gamma Telescope: Data are MC generated to simulate registration of high energy gamma particles in an atmospheric Cherenkov telescope
17. 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.
18. Madelon: MADELON is an artificial dataset, which was part of the NIPS 2003 feature selection challenge. This is a two-class classification problem with continuous input variables. The difficulty is that the problem is multivariate and highly non-linear.
19. Ozone Level Detection: Two ground ozone level data sets are included in this collection. One is the eight hour peak set (eighthr.data), the other is the one hour peak set (onehr.data). Those data were collected from 1998 to 2004 at the Houston, Galveston and Brazoria area.
20. Parkinsons: Oxford Parkinson's Disease Detection Dataset
21. Blood Transfusion Service Center: Data taken from the Blood Transfusion Service Center in Hsin-Chu City in Taiwan -- this is a classification problem.
22. SECOM: Data from a semi-conductor manufacturing process
23. Libras Movement: The data set contains 15 classes of 24 instances each. Each class references to a hand movement type in LIBRAS (Portuguese
name 'LÍngua BRAsileira de Sinais', oficial brazilian signal language).
24. Wine Quality: Two datasets are included, related to red and white vinho verde wine samples, from the north of Portugal. The goal is to model wine quality based on physicochemical tests (see [Cortez et al., 2009], http://www3.dsi.uminho.pt/pcortez/wine/).
25. p53 Mutants: The goal is to model mutant p53 transcriptional activity (active vs inactive) based on data extracted from biophysical simulations.
26. Breast Tissue: Dataset with electrical impedance measurements of freshly excised tissue samples from the breast.
27. Cardiotocography: The dataset consists of measurements of fetal heart rate (FHR) and uterine contraction (UC) features on cardiotocograms classified by expert obstetricians.
28. Wall-Following Robot Navigation Data: The data were collected as the SCITOS G5 robot navigates through the room following the wall in a clockwise direction, for 4 rounds, using 24 ultrasound sensors arranged circularly around its 'waist'.
29. Spoken Arabic Digit: This dataset contains timeseries of mel-frequency cepstrum coefficients (MFCCs) corresponding to spoken Arabic digits. Includes data from 44 male and 44 female native Arabic speakers.
30. MiniBooNE particle identification: This dataset is taken from the MiniBooNE experiment and is used to distinguish electron neutrinos (signal) from muon neutrinos (background).
31. PEMS-SF: 15 months worth of daily data (440 daily records) that describes the occupancy rate, between 0 and 1, of different car lanes of the San Francisco bay area freeways across time.
32. Record Linkage Comparison Patterns: Element-wise comparison of records with personal data from a record linkage setting. The task is to decide from a comparison pattern whether the underlying records belong to one person.
33. Vertebral Column: Data set containing values for six biomechanical features used to classify orthopaedic patients into 3 classes (normal, disk hernia or spondilolysthesis) or 2 classes (normal or abnormal).
34. Amazon Commerce reviews set: The dataset is used for authorship identification in online Writeprint which is a new research field of pattern recognition.
35. Reuter_50_50: The dataset is used for authorship identification in online Writeprint which is a new research field of pattern recognition.
36. Bank Marketing: The data is related with direct marketing campaigns (phone calls) of a Portuguese banking institution. The classification goal is to predict if the client will subscribe a term deposit (variable y).
37. Gas Sensor Array Drift Dataset: This archive contains 13910 measurements from 16 chemical sensors utilized in simulations for drift compensation in a discrimination task of 6 gases at various levels of concentrations.
38. OPPORTUNITY Activity Recognition: The OPPORTUNITY Dataset for Human Activity Recognition from Wearable, Object, and Ambient Sensors is a dataset devised to benchmark human activity recognition algorithms (classification, automatic data segmentation, sensor fusion, feature extraction, etc).
39. SMS Spam Collection: The SMS Spam Collection is a public set of SMS labeled messages that have been collected for mobile phone spam research.
40. PAMAP2 Physical Activity Monitoring: The PAMAP2 Physical Activity Monitoring dataset contains data of 18 different physical activities, performed by 9 subjects wearing 3 inertial measurement units and a heart rate monitor.
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. 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
43. 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.
44. ISTANBUL STOCK EXCHANGE: Data sets includes returns of Istanbul Stock Exchange with seven other international index; SP, DAX, FTSE, NIKKEI, BOVESPA, MSCE_EU, MSCI_EM from Jun 5, 2009 to Feb 22, 2011.
45. First-order theorem proving: Given a theorem, predict which of five heuristics will give the fastest proof when used by a first-order prover. A sixth prediction declines to attempt a proof, should the theorem be too difficult.
46. Gas sensor arrays in open sampling settings: The dataset contains 18000 time-series recordings from a chemical detection platform at six different locations in a wind tunnel facility in response to ten high-priority chemical gaseous substances
47. Ionosphere: Classification of radar returns from the ionosphere
48. Multiple Features: This dataset consists of features of handwritten numerals (`0'--`9') extracted from a collection of Dutch utility maps
49. Page Blocks Classification: The problem consists of classifying all the blocks of the page layout of a document that has been detected by a segmentation process.
50. Pima Indians Diabetes: From National Institute of Diabetes and Digestive and Kidney Diseases; Includes cost data (donated by Peter Turney)
51. Low Resolution Spectrometer: From IRAS data -- NASA Ames Research Center
52. Spambase: Classifying Email as Spam or Non-Spam
53. Wine: Using chemical analysis determine the origin of wines
54. URL Reputation: Anonymized 120-day subset of the ICML-09 URL data containing 2.4 million examples and 3.2 million features.
55. Steel Plates Faults: A dataset of steel platesâ€™ faults, classified into 7 different types.
The goal was to train machine learning for automatic pattern recognition.
56. 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.
57. KEGG Metabolic Relation Network (Directed): KEGG Metabolic pathways modeled as directed relation network. Variety of graphical features presented.
58. KEGG Metabolic Reaction Network (Undirected): KEGG Metabolic pathways modeled as un-directed reaction network. Variety of graphical features presented.
59. 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.
60. Northix: Northix is designed to be a schema matching benchmark problem for data integration of two entity relationship databases.
61. Energy efficiency: This study looked into assessing the heating load and cooling load requirements of buildings (that is, energy efficiency) as a function of building parameters.
62. Breast Cancer Wisconsin (Original): Original Wisconsin Breast Cancer Database
63. Haberman's Survival: Dataset contains cases from study conducted on the survival of patients who had undergone surgery for breast cancer
64. Letter Recognition: Database of character image features; try to identify the letter
65. Lung Cancer: Lung cancer data; no attribute definitions
66. Musk (Version 1): The goal is to learn to predict whether new molecules will be musks or non-musks
67. Musk (Version 2): The goal is to learn to predict whether new molecules will be musks or non-musks
68. Optical Recognition of Handwritten Digits: Two versions of this database available; see folder
69. Pen-Based Recognition of Handwritten Digits: Digit database of 250 samples from 44 writers
70. SPECTF Heart: Data on cardiac Single Proton Emission Computed Tomography (SPECT) images. Each patient classified into two categories: normal and abnormal.
71. Robot Execution Failures: This dataset contains force and torque measurements on a robot after failure detection. Each failure is characterized by 15 force/torque samples collected at regular time intervals
72. Statlog (Landsat Satellite): Multi-spectral values of pixels in 3x3 neighbourhoods in a satellite image, and the classification associated with the central pixel in each neighbourhood
73. Statlog (Shuttle): The shuttle dataset contains 9 attributes all of which are numerical. Approximately 80% of the data belongs to class 1
74. Statlog (Vehicle Silhouettes): 3D objects within a 2D image by application of an ensemble of shape feature extractors to the 2D silhouettes of the objects.
75. UJI Pen Characters: Data consists of written characters in a UNIPEN-like format
76. Mammographic Mass: Discrimination of benign and malignant mammographic masses based on BI-RADS attributes and the patient's age.
77. Dexter: DEXTER is a text classification problem in a bag-of-word representation. This is a two-class classification problem with sparse continuous input variables. This dataset is one of five datasets of the NIPS 2003 feature selection challenge.
78. 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.
79. Gisette: GISETTE is a handwritten digit recognition problem. The problem is to separate the highly confusible digits '4' and '9'. This dataset is one of five datasets of the NIPS 2003 feature selection challenge.
80. UJI Pen Characters (Version 2): A pen-based database with more than 11k isolated handwritten characters
81. Semeion Handwritten Digit: 1593 handwritten digits from around 80 persons were scanned, stretched in a rectangular box 16x16 in a gray scale of 256 values.
82. Demospongiae: Marine sponges of the Demospongiae class classification domain.
83. Online Handwritten Assamese Characters Dataset: This is a dataset of 8235 online handwritten assamese characters. The â€śonlineâ€ť process involves capturing of data as text is written on a digitizing tablet with an electronic pen.
84. CNAE-9: This is a data set containing 1080 documents of free text business descriptions of Brazilian companies categorized into a
subset of 9 categories