long-4 dataset

1: Description.

This dataset is used to predict whether an athlete will improve certain threshold in the long jump (class label 1) or not (class label 0), given the following indicators (attributes): 

1) Indicator 1: the ratio between the weight and the height. 
2) Indicator 2: the maximum speed in the 40 m race. 
3) Indicator 3: the test of central (abdominal) muscles. 
4) Indicator 4: the test of lower extremities. 

The first two indicators are determined by the coach, who was allowed to use numbers, intervals or linguistic values (fuzzy intervals) at his convenience. 

The two last tests are repeated three times, and produce numbers. The abdominal muscle test consists in counting how many flexion movements the athlete can repeat in a minute. Lastly, the lower extremities test measures how much the athlete can stretch. 

There are 25 athletes, thus the set has 25 instances, 4 features, 2 classes, no missing values. All the features, and also the output variable, are intervalvalued.

2: Type.			Low quality
3: Origin.			Laboratory
4: Instances.		25
5: Features.		4
6: Missing values.	No
7: Header.
@relation Long4
@attribute Indicator1 interval [0, 20]
@attribute Indicator2 interval [0, 100]
@attribute Indicator3 interval [0, 10]
@attribute Indicator4 interval [0, 10]
@attribute Class subset {0, 1}
@inputs Indicator1, Indicator2, Indicator3, Indicator4
@outputs Class