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

Thyroid Disease (thyroid0387) data set

Description
Files and additional references

Description

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

General information

Thyroid Disease (thyroid0387) data set
Type	Classification	Origin	Real world
Features	21	(Real / Integer / Nominal)	(6 / 15 / 0)
Instances	7200	Classes	3
Missing values?			No

Attribute description

Attribute	Domain	Attribute	Domain	Attribute	Domain
Age	[0.01, 0.97]	Thyroid_surgery	[0, 1]	Hypopituitary	[0, 1]
Sex	[0, 1]	I131_treatment	[0, 1]	Psych	[0, 1]
On_thyroxine	[0, 1]	Query_hypothyroid	[0, 1]	TSH	[0.0, 0.53]
Query_on_thyroxine	[0, 1]	Query_hyperthyroid	[0, 1]	T3	[0.0005, 0.18]
On_antithyroid_medication	[0, 1]	Lithium	[0, 1]	TT4	[0.0020, 0.6]
Sick	[0, 1]	Goitre	[0, 1]	T4U	[0.017, 0.233]
Pregnant	[0, 1]	Tumor	[0, 1]	FTI	[0.0020, 0.642]
Class	{1,2,3}

Additional information

This data set is one of the several databases about Thyroid avalaible at the UCI repository. The task is to detect is a given patient is normal (1) or suffers from hyperthyroidism (2) or hypothyroidism (3)

Files and additional references

In this section you can download some files related to the thyroid 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 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/Thyroid+Disease.