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


Repository Web            Google
View ALL Data Sets

× Check out the beta version of the new UCI Machine Learning Repository we are currently testing! Contact us if you have any issues, questions, or concerns. Click here to try out the new site.

Browse Through:

Default Task

Classification (3)
Regression (6)
Clustering (1)
Other (0)

Attribute Type - Undo

Categorical (1)
Numerical (9)
Mixed (0)

Data Type

Multivariate (8)
Univariate (0)
Sequential (0)
Time-Series (1)
Text (0)
Domain-Theory (0)
Other (0)

Area - Undo

Life Sciences (21)
Physical Sciences (9)
CS / Engineering (26)
Social Sciences (0)
Business (9)
Game (0)
Other (4)

# Attributes - Undo

Less than 10 (9)
10 to 100 (25)
Greater than 100 (3)

# Instances

Less than 100 (1)
100 to 1000 (3)
Greater than 1000 (5)

Format Type - Undo

Matrix (9)
Non-Matrix (2)

9 Data Sets

Table View  List View


1. Challenger USA Space Shuttle O-Ring: Task: predict the number of O-rings that experience thermal distress on a flight at 31 degrees F given data on the previous 23 shuttle flights

2. Airfoil Self-Noise: NASA data set, obtained from a series of aerodynamic and acoustic tests of two and three-dimensional airfoil blade sections conducted in an anechoic wind tunnel.

3. Yacht Hydrodynamics: Delft data set, used to predict the hydodynamic performance of sailing yachts from dimensions and velocity.

4. QSAR fish toxicity: Data set containing values for 6 attributes (molecular descriptors) of 908 chemicals used to predict quantitative acute aquatic toxicity towards the fish Pimephales promelas (fathead minnow).

5. EMG Physical Action Data Set: The Physical Action Data Set includes 10 normal and 10 aggressive physical actions that measure the human activity. The data have been collected by 4 subjects using the Delsys EMG wireless apparatus.

6. HTRU2: Pulsar candidates collected during the HTRU survey. Pulsars are a type of star, of considerable scientific interest. Candidates must be classified in to pulsar and non-pulsar classes to aid discovery.

7. Statlog (Shuttle): The shuttle dataset contains 9 attributes all of which are numerical. Approximately 80% of the data belongs to class 1

8. Concrete Compressive Strength: Concrete is the most important material in civil engineering. The concrete compressive strength is a highly nonlinear function of age and ingredients.

9. QSAR aquatic toxicity: Data set containing values for 8 attributes (molecular descriptors) of 546 chemicals used to predict quantitative acute aquatic toxicity towards Daphnia Magna..


Supported By:

 In Collaboration With:

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