dermatology: Dermatology Database

In ICGE: Estimation of Number of Clusters and Identification of Atypical Units

Dermatology Database

Description

Data from a dermatology study provided by H.A. Guvenir (Dpt. Computer Engineering and Information Science, Bilkent University, Turkey).The data set contains 366 instances presenting 34 different clinical attributes (12 clinical features as age or family history and 22 histopathological features obtained from a biopsy), and a class variable indicating the disease. There are 8 missing values. This data set has been used extensively for classification tasks.

Usage

data(dermatology)

Format

Matrix with 366 rows.

Details

Attribute information obtained from the UCI KDD data repository:

Clinical Attributes: (they take values 0, 1, 2, 3, unless otherwise indicated)

1: erythema; 2: scaling; 3: definite borders; 4: itching; 5: koebner phenomenon; 6: polygonal papules; 7: follicular papules; 8: oral mucosal involvement; 9: knee and elbow involvement; 10: scalp involvement; 11: family history, (0 or 1); 34: Age.

Histopathological Attributes: (they take values 0, 1, 2, 3)

12: melanin incontinence; 13: eosinophils in the infiltrate; 14: PNL infiltrate; 15: fibrosis of the papillary dermis; 16: exocytosis; 17: acanthosis; 18: hyperkeratosis; 19: parakeratosis; 20: clubbing of the rete ridges; 21: elongation of the rete ridges; 22: thinning of the suprapapillary epidermis; 23: spongiform pustule; 24: munro microabcess; 25: focal hypergranulosis; 26: disappearance of the granular layer; 27: vacuolisation and damage of basal layer; 28: spongiosis; 29: saw-tooth appearance of retes; 30: follicular horn plug; 31: perifollicular parakeratosis; 32: inflammatory monoluclear inflitrate; 33: band-like infiltrate.

The considered diseases are: 1 - psoriasis, 2 - seboreic dermatitis, 3- lichen planus, 4 - pityriasis rosea, 5 - chronic dermatitis, 6 - pityriasis rubra pilaris.

Source

The UCI KDD Archive.

References

Guvenir H, Demiroz G, Ilter N (1998). Learning differential diagnosis of erythemato-squamous diseases using voting feature intervals. Artificial Intelligence in Medicine, 13, 147–165.

Irigoien I, Arenas C (2008). INCA: New statistic for estimating the number of clusters and identifying atypical units. Statistics in Medicine, 27, 2948–2973.

Examples

data(dermatology)
x <- dermatology[, 1:34]
group <- as.factor(dermatology[,35])

plot(group)

ICGE documentation built on Oct. 17, 2022, 5:10 p.m.