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

Credit Approval data set

Description
Files and additional references

Description

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

General information

Credit Approval data set
Type	Classification	Origin	Real world
Features	15	(Real / Integer / Nominal)	(3 / 3 / 9)
Classes	2	Missing values?	Yes
Total instances	690	Instances without missing values	653

Attribute description

Attribute	Domain	Attribute	Domain
A1	{b, a}	A9	{t, f}
A2	[16.0, 8025.0]	A10	{t, f}
A3	[0.0, 26335.0]	A11	[0, 67]
A4	{u, y, l}	A12	{f, t}
A5	{g, p, gg}	A13	{g, s, p}
A6	{w, q, m, r, cc, k, c, d, x, i, e, aa, ff, j}	A14	[0, 2000]
A7	{v, h, bb, ff, j, z, o, dd, n}	A15	[0, 100000]
A8	[0.0, 14415.0]	Class	{positive, negative}

Additional information

This file concerns credit card applications. All attribute names and values have been changed to meaningless symbols to protect confidentiality of the data.

This data set is interesting because there is a good mix of attributes: continuous, nominal with small numbers of values, and nominal with larger numbers of values. This data set is a extended version of the Australian data set (it has one more attribute, A8).

Files and additional references

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

The complete data set already formatted in KEEL formatcan be downloaded from here .
A copy of the data set already partitioned by means of a 10-folds cross validation procedure 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/Credit+Approval.