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

Classification (37)
Regression (8)
Clustering (4)
Other (7)

Attribute Type

Categorical (4)
Numerical (27)
Mixed (5)

Data Type

Multivariate (29)
Univariate (2)
Sequential (2)
Time-Series (5)
Text (5)
Domain-Theory (4)
Other (4)

Area

Life Sciences (11)
Physical Sciences (4)
CS / Engineering (17)
Social Sciences (3)
Business (2)
Game (0)
Other (8)

# Attributes

Less than 10 (7)
10 to 100 (21)
Greater than 100 (6)

# Instances - Undo

Less than 100 (7)
100 to 1000 (45)
Greater than 1000 (72)

Format Type - Undo

Matrix (122)
Non-Matrix (45)

45 Data Sets

Table View  List View


1. 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.

2. Alcohol QCM Sensor Dataset: Five different QCM gas sensors are used, and five different gas measurements (1-octanol, 1-propanol, 2-butanol, 2-propanol and 1-isobutanol) are conducted in each of these sensors.

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

4. Autism Screening Adult: Autistic Spectrum Disorder Screening Data for Adult. This dataset is related to classification and predictive tasks.

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

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

7. Bach Chorales: Time-series data based on chorales; challenge is to learn generative grammar; data in Lisp

8. Behavior of the urban traffic of the city of Sao Paulo in Brazil: The database was created with records of behavior of the urban traffic of the city of Sao Paulo in Brazil.

9. Chronic_Kidney_Disease: This dataset can be used to predict the chronic kidney disease and it can be collected from the hospital nearly 2 months of period.

10. CMU Face Images: This data consists of 640 black and white face images of people taken with varying pose (straight, left, right, up), expression (neutral, happy, sad, angry), eyes (wearing sunglasses or not), and size

11. Connectionist Bench (Vowel Recognition - Deterding Data): Speaker independent recognition of the eleven steady state vowels of British English using a specified training set of lpc derived log area ratios.

12. CSM (Conventional and Social Media Movies) Dataset 2014 and 2015: 12 features categorized as conventional and social media features. Both conventional features, collected from movies databases on Web as well as social media features(YouTube,Twitter).

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

14. Dresses_Attribute_Sales: This dataset contain Attributes of dresses and their recommendations according to their sales.Sales are monitor on the basis of alternate days.

15. ElectricityLoadDiagrams20112014: This data set contains electricity consumption of 370 points/clients.

16. EMG dataset in Lower Limb: 3 different exercises: sitting, standing and walking in the muscles: biceps femoris, vastus medialis, rectus femoris and semitendinosus addition to goniometry in the exercises.

17. 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

18. Folio: 20 photos of leaves for each of 32 different species.

19. 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.

20. Function Finding: Cases collected mostly from investigations in physical science; intention is to evaluate function-finding algorithms

21. GPS Trajectories: The dataset has been feed by Android app called Go!Track. It is available at Goolge Play Store(https://play.google.com/store/apps/details?id=com.go.router).

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

23. Hill-Valley: Each record represents 100 points on a two-dimensional graph. When plotted in order (from 1 through 100) as the Y co-ordinate, the points will create either a Hill (a “bump” in the terrain) or a Valley (a “dip” in the terrain).

24. 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.

25. Japanese Credit Screening: Includes domain theory (generated by talking to Japanese domain experts); data in Lisp

26. Kinship: Relational dataset

27. Low Resolution Spectrometer: From IRAS data -- NASA Ames Research Center

28. Mechanical Analysis: Fault diagnosis problem of electromechanical devices; also PUMPS DATA SET is newer version with domain theory and results

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

30. Moral Reasoner: Horn-clause model that qualitatively simulates moral reasoning; Theory includes negated literals

31. Newspaper and magazine images segmentation dataset: Dataset is well suited for segmentation tasks. It contains 101 scanned pages from different newspapers and magazines in Russian with ground truth pixel-based masks.

32. NoisyOffice: Corpus intended to do cleaning (or binarization) and enhancement of noisy grayscale printed text images using supervised learning methods. Noisy images and their corresponding ground truth provided.

33. Northix: Northix is designed to be a schema matching benchmark problem for data integration of two entity relationship databases.

34. Paper Reviews: This sentiment analysis data set contains scientific paper reviews from an international conference on computing and informatics. The task is to predict the orientation or the evaluation of a review.

35. Reuters Transcribed Subset: This dataset is created by reading out 200 files from the 10 largest Reuters classes and using an Automatic Speech Recognition system to create corresponding transcriptions.

36. Rice Leaf Diseases: There are three classes/diseases: Bacterial leaf blight, Brown spot, and Leaf smut, each having 40 images. The format of all images is jpg.

37. 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

38. ser Knowledge Modeling Data (Students' Knowledge Levels on DC Electrical Machines): The dataset is about the users' learning activities and knowledge levels on subjects of DC Electrical Machines. The dataset had been obtained from online web-courses and reported in my Ph.D. Thesis.

39. Student Academics Performance: The dataset tried to find the end semester percentage prediction based on different social, economic and academic attributes.

40. Student Loan Relational: Student Loan Relational Domain

41. Syskill and Webert Web Page Ratings: This database contains HTML source of web pages plus the ratings of a single user on these web pages. Web pages are on four seperate subjects (Bands- recording artists; Goats; Sheep; and BioMedical)

42. 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.

43. University: Data in original (LISP-readable) form

44. Urban Land Cover: Classification of urban land cover using high resolution aerial imagery. Intended to assist sustainable urban planning efforts.

45. USPTO Algorithm Challenge, run by NASA-Harvard Tournament Lab and TopCoder Problem: Pat: Data used for USPTO Algorithm Competition. Contains drawing pages from US patents with manually labeled figure and part labels.


Supported By:

 In Collaboration With:

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