MONK's Problem 2 data set

1: Description.

The MONK's problems are a collection of three binary classification problems (MONK-1, MONK-2 and MONK-3) over a six-attribute discrete domain. Each problem involves learning a binary function defined over this domain, from a sample of training examples that belong to class 0 or class 1. 

This is the second problem of the collection, with no random noise added.

2: Type.			Classification	
3: Origin.			Laboratory
4: Instances.		432
5: Features.		6
6: Classes.			2	
7: Missing values.	No

8: Header.

@relation monk-2
@attribute A1 integer [1, 3]
@attribute A2 integer [1, 3]
@attribute A3 integer [1, 2]
@attribute A4 integer [1, 3]
@attribute A5 integer [1, 4]
@attribute A6 integer [1, 2]
@attribute Class {0,1}
@inputs A1, A2, A3, A4, A5, A6
@outputs Class