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 - Undo

Categorical (1)
Numerical (7)
Mixed (0)

Data Type - Undo

Multivariate (29)
Univariate (2)
Sequential (7)
Time-Series (11)
Text (5)
Domain-Theory (1)
Other (3)

Area - Undo

Life Sciences (4)
Physical Sciences (1)
CS / Engineering (27)
Social Sciences (0)
Business (6)
Game (0)
Other (7)

# Attributes

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

# Instances

Less than 100 (0)
100 to 1000 (2)
Greater than 1000 (3)

Format Type

Matrix (5)
Non-Matrix (2)

7 Data Sets

Table View  List View


1. Activity Recognition from Single Chest-Mounted Accelerometer: The dataset collects data from a wearable accelerometer mounted on the chest. The dataset is intended for Activity Recognition research purposes.

2. Gesture Phase Segmentation: The dataset is composed by features extracted from 7 videos with people gesticulating, aiming at studying Gesture Phase Segmentation. It contains 50 attributes divided into two files for each video.

3. 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).

4. Human Activity Recognition from Continuous Ambient Sensor Data: This dataset represents ambient data collected in homes with volunteer residents. Data are collected continuously while residents perform their normal routines.

5. 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).

6. Metro Interstate Traffic Volume: Hourly Minneapolis-St Paul, MN traffic volume for westbound I-94. Includes weather and holiday features from 2012-2018.

7. User Identification From Walking Activity: The dataset collects data from an Android smartphone positioned in the chest pocket from 22 participants walking in the wild over a predefined path.


Supported By:

 In Collaboration With:

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