Browse Through:

Default Task - Undo

Classification (2)
Regression (0)
Clustering (0)
Other (0)

Attribute Type

Categorical (0)
Numerical (2)
Mixed (0)

Data Type - Undo

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

Area - Undo

Life Sciences (2)
Physical Sciences (1)
CS / Engineering (11)
Social Sciences (0)
Business (1)
Game (0)
Other (2)

# Attributes - Undo

Less than 10 (3)
10 to 100 (5)
Greater than 100 (2)

# Instances - Undo

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

Format Type - Undo

Matrix (2)
Non-Matrix (0)

2 Data Sets

Table View  List View

1. Dorothea: DOROTHEA is a drug discovery dataset. Chemical compounds represented by structural molecular features must be classified as active (binding to thrombin) or inactive. This is one of 5 datasets of the NIPS 2003 feature selection challenge.

2. p53 Mutants: The goal is to model mutant p53 transcriptional activity (active vs inactive) based on data extracted from biophysical simulations.