Naslov
Support Vector Machine Optimized by Elephant Herding Algorithm for Erythemato-Squamous Diseases Detection

Autori
Tuba, Eva ; Ribic, Ivana ; Capor-Hrosik, Romana ; Tuba, Milan

Izvornik
Procedia computer science (1877-0509) 122 (2017); 916-923

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
elephant herding algorithm ; EHO ; support vector machine ; SVM ; erythemato-squamous diseases

Sažetak
Machine learning algorithms are used in numerous field and medicine is one of them. Automatic diagnosis or detection of different diseases based on list of symptoms can drastically improve and speedup diagnostics process. Determining diagnosis at earlier stages gives better healing results. In this paper a method for automatic erythemato- squamous diseases classification was proposed. Six erythemato-squamous diseases that are very hard to distinguish were classified by the optimized support vector machine. Recent swarm intelligent algorithm, elephant herding optimization algorithm was used to find optimal parameters for the support vector machine that was then used to determine the exact erythemato-squamous diseases. We compared accuracy of our proposed method to other approaches from literature using standard dataset and it obtained better results in all experiments.

Izvorni jezik
Engleski

Znanstvena područja
Matematika, Računarstvo

POVEZANOST RADA