Implementacija i primjena algoritma stroja potpornih vektora u klasifikaciji i regresiji

master's thesis

• Title (english): Implementation and Application of Support Vector Machine to Classification and Regression
• Author: Ivan Ćorić
• Mentor: Domagoj Jakobović (mentor)
• Committee member: Domagoj Jakobović (predsjednik povjerenstva)
• Committee member: Marko Čupić (član povjerenstva)
• Committee member: Leonardo Jelenković (član povjerenstva)
• Granter: University of Zagreb; Faculty of Electrical Engineering and Computing; Zagreb
• Defense date and country: 2018-09-21, Croatia
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Computing

Abstract

Opisana je teorija iza algoritma stroja potpornih vektora, kako za klasifikaciju, tako i za regresiju. Opisan je algoritam sekvencijalne minimalne organizacije. Napravljena je implementacija algoritma i za klasifikaciju i za regresiju te su oba algoritma primijenjena na nekoliko skupova podataka. Napravljena je usporedba naše implementacije s drugim implementacijama te su rezultati zadovoljavajući.

Abstract (english)

In this paper, support vector machine (SVM) algorithm for classification and regression is described. Sequential minimal optimization (SMO) algorithm was also described and used for optimization. The implementation of SVM algorithm for classification and regression has been made. The implementation was tested and compared to other implementations and the results are satisfying.

• Keywords: Stroj potpornih vektora; klasifikacija; regresija; sekvencijalna mini-malna optimizacija
• Keywords (english): Support vector machine; SVM; SVC; SVR; classification; regression; Sequential minimal optimization; SMO
• Language: croatian
• URN:NBN: urn:nbn:hr:168:357242
• Study programme: Title: Computing; Study programme type: university; Study level: graduate; Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Closed access
• Created on: 2019-03-13 19:51:07