A Novel Diagnostic Approach Based on Support Vector Machine with Linear Kernel for classifying the erythemato-squamous disease

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F15%3A86099386" target="_blank" >RIV/61989100:27240/15:86099386 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1109/ICCUBEA.2015.72D" target="_blank" >http://dx.doi.org/10.1109/ICCUBEA.2015.72D</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/ICCUBEA.2015.72D" target="_blank" >10.1109/ICCUBEA.2015.72D</a>

Jazyk výsledku

angličtina

Název v původním jazyce

A Novel Diagnostic Approach Based on Support Vector Machine with Linear Kernel for classifying the erythemato-squamous disease

Popis výsledku v původním jazyce

The diagnosis of the arythema disease is a real difficulty in dermatology. It causes redness induced in the lower level of the skin by hyperemia of the capillaries. It can harm several skin damages, inflammations. In this paper, we have put our efforts to design a diagnostic approach based on Support Vector Machine (SVM) with linear kernel by classifying the erythemato-squamous disease. SVM being a large margin classifier is a powerful pattern recognition and machine learning methodology that is widely used for both linear and non-linear classification problems. Comparing testing on different kernel methods, we have noticed that our method gives the better accuracy. Choosing the optimal value of the parameters is a crucial criterion and this was achieved by performing 3 fold cross-validations. (C) 2015 IEEE.

Název v anglickém jazyce

A Novel Diagnostic Approach Based on Support Vector Machine with Linear Kernel for classifying the erythemato-squamous disease

Popis výsledku anglicky

The diagnosis of the arythema disease is a real difficulty in dermatology. It causes redness induced in the lower level of the skin by hyperemia of the capillaries. It can harm several skin damages, inflammations. In this paper, we have put our efforts to design a diagnostic approach based on Support Vector Machine (SVM) with linear kernel by classifying the erythemato-squamous disease. SVM being a large margin classifier is a powerful pattern recognition and machine learning methodology that is widely used for both linear and non-linear classification problems. Comparing testing on different kernel methods, we have noticed that our method gives the better accuracy. Choosing the optimal value of the parameters is a crucial criterion and this was achieved by performing 3 fold cross-validations. (C) 2015 IEEE.

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

—

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2015

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings - 1st International Conference on Computing, Communication, Control and Automation, ICCUBEA 2015

ISBN

978-1-4799-6892-3

ISSN

—

e-ISSN

—

Počet stran výsledku

5

Strana od-do

343-347

Název nakladatele

Institute of Electrical and Electronics Engineers

Místo vydání

New York

Místo konání akce

Pune

Datum konání akce

26. 2. 2015

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000380620000067