University of Zagreb. Faculty of Science. Department of Mathematics.
Abstract
Prvo poglavlje ovoga rada uvodi pojam strojnoga učenja, kao i njegovu povijest i primjenu. Sljedeća dva poglavlja uvode regresiju i klasifikaciju te algoritme linearne regresije i logističke regresije koji služe kao mjerilo usporedbe algoritmu potpornih vektora, koji je glavna tematika ovoga rada. Naposljetku slijedi usporedba metode potpornih vektora sa spomenutim metodama logističke regresije i linearne regresije na konkretnom klasifikacijskom i regresijskom problemu.The first chapter of this work introduces the concept of machine learning, as well as its history and applications. The next two chapters focus on the concept of regression and classification as well as the appropriate algorithms, linear regression and logistic regression. The aforementioned algorithms are used as a baseline for the main algorithm of this work: the support vector machine algorithm which is talked about in detail in the next chapter. In conclusion, the methods are compared on a concrete regression and classification problem