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

Forest Fires data set

Description
Files and additional references

Description

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

General information

Forest Fires data set
Type	Regression	Origin	Real world
Features	12	(Real / Integer / Nominal)	(7 / 5 / 0)
Instances	517	Missing values?	No

Attribute description

Attribute	Domain	Attribute	Domain
X	[1,9]	DC	[7.9,860.6]
Y	[2,9]	ISI	[0,56.1]
Month	[1,12]	Temp	[2.2,33.3]
Day	[1,7]	RH	[15,100]
FFMC	[18.7,96.2]	Wind	[0.4,9.4]
DMC	[1.1,291.3]	Rain	[0,6.4]
Area	[0,1090.84]

Additional information

This is a difficult regression task, where the aim is to predict the burned area of forest fires, in the northeast region of Portugal, by using meteorological and other data.

Files and additional references

In this section you can download some files related to the forestFires 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 UCI Machine Learning Repository. The original page where the data set can be found is: http://archive.ics.uci.edu/ml/datasets/Forest+Fires.