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

Dermatology data set

Description
Files and additional references

Description

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

General information

Dermatology data set
Type	Classification	Origin	Real world
Features	34	(Real / Integer / Nominal)	(0 / 34 / 0)
Classes	6	Missing values?	Yes
Total instances	366	Instances without missing values	358

Attribute description

Attribute	Domain	Attribute	Domain	Attribute	Domain
Erythema	[0,3]	Eosinophils	[0,2]	Munro_microabcess	[0,3]
Scaling	[0,3]	PNL_infiltrate	[0,3]	Focal_hypergranulosis	[0,3]
Definite_borders	[0,3]	Fibrosis	[0,3]	Granular_layer	[0,3]
Itching	[0,3]	Exocytosis	[0,3]	Vacuolisation	[0,3]
Koebner_phenomenon	[0,3]	Acanthosis	[0,3]	Spongiosis	[0,3]
Polygonal_papules	[0,3]	Hyperkeratosis	[0,3]	Saw-tooth_appearance	[0,3]
Follicular_papules	[0,3]	Parakeratosis	[0,3]	Follicular_horn_plug	[0,3]
Oral_mucosal	[0,3]	Clubbing	[0,3]	Perifollicular_parakeratosis	[0,3]
Knee_and_elbow	[0,3]	Elongation	[0,3]	Inflammatory_monoluclear	[0,3]
Scalp_involvement	[0,3]	Thinning	[0,3]	Band-like_infiltrate	[0,3]
Family_history	[0,1]	Spongiform_pustule	[0,3]	Age	[0,75]
Melanin_incontinence	[0,3]	Class	{1,2,3,4,5,6}

Additional information

The differential diagnosis of erythemato-squamous diseases is a real problem in dermatology. Patients were first evaluated clinically with 12 features. Afterwards, skin samples were taken for the evaluation of 22 histopathological features.

In the dataset constructed for this domain, the family history feature has the value 1 if any of these diseases has been observed in the family, and 0 otherwise. The age feature simply represents the age of the patient. Every other feature (clinical and histopathological) was given a degree in the range of 0 to 3. Here, 0 indicates that the feature was not present, 3 indicates the largest amount possible, and 1, 2 indicate the relative intermediate values.

Files and additional references

In this section you can download some files related to the dermatology 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/Dermatology.