KEEL: A software tool to assess evolutionary algorithms for Data Mining problems (regression, classification, clustering, pattern mining and so on)

KEEL-dataset - data set description

Friedman Benchmark Function data set

Description
Files and additional references

Description

This section describes main characteristics of the friedman data set and its attributes:

General information

Friedman Benchmark Function data set
Type	Regression	Origin	Laboratory
Features	5	(Real / Integer / Nominal)	(5 / 0 / 0)
Instances	1200	Missing values?	No

Attribute description

Attribute	Domain
Input1	[0.0, 1.0]
Input2	[0.0, 1.0]
Input3	[0.0, 1.0]
Input4	[0.0, 1.0]
Input5	[0.0, 1.0]
Output	[0.664014955, 28.5903858]

Additional information

This is a synthetic benchmark dataset proposed by Friedman in 1991.

The cases are generated using the following method:

Generate the values of 5 attributes, X1, ..., X5 independently each of which uniformly distributed over [0.0, 1.0]. Obtain the value of the target variable Y using the equation:

y=10(sin(PI)x1x2)+20(x3-0.5)2+10x4+5x5+e

where e is a Gaussian random noise N(0,1).

Files and additional references

In this section you can download some files related to the friedman data set:

The complete data set already formatted in KEEL format can be downloaded from here .
A copy of the data set already partitioned by means of a 5-folds cross validation procedure can be downloaded from here .
The header file associated to this data set can be downloaded from here .
This is not a native data set from the KEEL project. It has been obtained from the LIACC repository. The original page where the data set can be found is: http://www.liaad.up.pt/~ltorgo/Regression/DataSets.html.