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 (4)
Regression (2)
Clustering (1)
Other (2)

Attribute Type - Undo

Categorical (0)
Numerical (8)
Mixed (0)

Data Type

Multivariate (6)
Univariate (0)
Sequential (0)
Time-Series (3)
Text (1)
Domain-Theory (1)
Other (2)

Area - Undo

Life Sciences (19)
Physical Sciences (8)
CS / Engineering (36)
Social Sciences (3)
Business (2)
Game (0)
Other (11)

# Attributes

Less than 10 (1)
10 to 100 (3)
Greater than 100 (3)

# Instances

Less than 100 (0)
100 to 1000 (3)
Greater than 1000 (5)

Format Type - Undo

Matrix (32)
Non-Matrix (8)

8 Data Sets

Table View  List View


1. Amazon Commerce reviews set: The dataset is used for authorship identification in online Writeprint which is a new research field of pattern recognition.

2. El Nino: The data set contains oceanographic and surface meteorological readings taken from a series of buoys positioned throughout the equatorial Pacific.

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

4. Greenhouse Gas Observing Network: Design an observing network to monitor emissions of a greenhouse gas (GHG) in California given time series of synthetic observations and tracers from weather model simulations.

5. Individual household electric power consumption: Measurements of electric power consumption in one household with a one-minute sampling rate over a period of almost 4 years. Different electrical quantities and some sub-metering values are available.

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

7. 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

8. Steel Plates Faults: A dataset of steel plates’ faults, classified into 7 different types. The goal was to train machine learning for automatic pattern recognition.


Supported By:

 In Collaboration With:

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