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

Abalone (Regression version) data set

Description
Files and additional references

Description

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

General information

Abalone (Regression version) data set
Type	Regression	Origin	Real world
Features	8	(Real / Integer / Nominal)	(7 / 1 / 0)
Instances	4177	Missing values?	No

Attribute description

Attribute	Domain
Sex	[1,3]
Length	[0.075, 0.815]
Diameter	[0.055, 0.65]
Height	[0.0, 1.13]
Whole_weight	[0.0020, 2.8255]
Shucked_weight	[0.0010, 1.488]
Viscera_weight	[0.0005, 0.76]
Shell_weight	[0.0015, 1.005]
Rings	[1,29]

Additional information

Predicting the age of abalone from physical measurements. The age of abalone is determined by cutting the shell through the cone and counting the number of rings through a microscope. Other measurements, which are easier to obtain, are used to predict the age. Further information, such as weather patterns and location (hence food availability) may be required to solve the problem.

This is a regression version of the original data set, where the output should be treated as a continuous value.

Files and additional references

In this section you can download some files related to the abalone 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/Abalone.