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 (6)
Regression (1)
Clustering (4)
Other (0)

Attribute Type

Categorical (0)
Numerical (7)
Mixed (0)

Data Type - Undo

Multivariate (9)
Univariate (2)
Sequential (6)
Time-Series (7)
Text (5)
Domain-Theory (1)
Other (0)

Area - Undo

Life Sciences (3)
Physical Sciences (1)
CS / Engineering (7)
Social Sciences (0)
Business (1)
Game (1)
Other (0)

# Attributes - Undo

Less than 10 (7)
10 to 100 (5)
Greater than 100 (3)

# Instances - Undo

Less than 100 (0)
100 to 1000 (1)
Greater than 1000 (7)

Format Type - Undo

Matrix (5)
Non-Matrix (7)

7 Data Sets

Table View  List View

1. Taxi Service Trajectory - Prediction Challenge, ECML PKDD 2015: An accurate dataset describing trajectories performed by all the 442 taxis running in the city of Porto, in Portugal.

2. Indoor User Movement Prediction from RSS data: This dataset contains temporal data from a Wireless Sensor Network deployed in real-world office environments. The task is intended as real-life benchmark in the area of Ambient Assisted Living.

3. Activity Recognition system based on Multisensor data fusion (AReM): This dataset contains temporal data from a Wireless Sensor Network worn by an actor performing the activities: bending, cycling, lying down, sitting, standing, walking.

4. Parking Birmingham: Data collected from car parks in Birmingham that are operated by NCP from Birmingham City Council. UK Open Government Licence (OGL).

5. 3W dataset: The first realistic and public dataset with rare undesirable real events in oil wells.

6. WISDM Smartphone and Smartwatch Activity and Biometrics Dataset : Contains accelerometer and gyroscope time-series sensor data collected from a smartphone and smartwatch as 51 test subjects perform 18 activities for 3 minutes each.

7. selfBACK: The SELFBACK dataset is a Human Activity Recognition Dataset of 9 activity classes recorded with two tri-axial accelerometers.

Supported By:

 In Collaboration With:

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