KEEL: A software tool to assess evolutionary algorithms for Data Mining problems (regression, classification, clustering, pattern mining and so on)

This section describes main characteristics of the dermatology-6 data set and its attributes:

General information

Dermatology (Imbalanced: 6 vs rest) data set
Type	Imbalanced	Origin	Real world
Features	34	(Real / Integer / Nominal)	(0 / 34 / 0)
Instances	358	IR	16.9
% Positive instances	5.59	% Negative instances	94.41
Missing values?	No

Attribute description

Attribute	Domain	Attribute	Domain	Attribute	Domain
Erythema	[0.0,3.0]	Eosinophils	[0.0,2.0]	Munro_microabcess	[0.0,3.0]
Scaling	[0.0,3.0]	PNL_infiltrate	[0.0,3.0]	Focal_hypergranulosis	[0.0,3.0]
Definite_borders	[0.0,3.0]	Fibrosis	[0.0,3.0]	Granular_layer	[0.0,3.0]
Itching	[0.0,3.0]	Exocytosis	[0.0,3.0]	Vacuolisation	[0.0,3.0]
Koebner_phenomenon	[0.0,3.0]	Acanthosis	[0.0,3.0]	Spongiosis	[0.0,3.0]
Polygonal_papules	[0.0,3.0]	Hyperkeratosis	[0.0,3.0]	Saw-tooth_appearance	[0.0,3.0]
Follicular_papules	[0.0,3.0]	Parakeratosis	[0.0,3.0]	Follicular_horn_plug	[0.0,3.0]
Oral_mucosal	[0.0,3.0]	Clubbing	[0.0,3.0]	Perifollicular_parakeratosis	[0.0,3.0]
Knee_and_elbow	[0.0,3.0]	Elongation	[0.0,3.0]	Inflammatory_monoluclear	[0.0,3.0]
Scalp_involvement	[0.0,3.0]	Thinning	[0.0,3.0]	Band-like_infiltrate	[0.0,3.0]
Family_history	[0.0,1.0]	Spongiform_pustule	[0.0,3.0]	Age	[0.0,75.0]
Melanin_incontinence	[0.0,3.0]	Class	{positive, negative}

Additional information

An imbalanced version of the Dermatology data set, where the possitive examples belong to the class 6 and the negative examples to the rest of the classes.

In this section you can download some files related to the dermatology-6 data set: