Napredni algoritmi stabala odluke

undergraduate thesis

• Title (english): Decision Trees
• Author: Jan Juričić
• Mentor: Vladimir Čeperić (mentor)
• Committee member: Vladimir Čeperić (predsjednik povjerenstva)
• Committee member: Zoran Medić (član povjerenstva)
• Committee member: Igor Stančin (član povjerenstva)
• Granter: University of Zagreb; Faculty of Electrical Engineering and Computing; Zagreb
• Defense date and country: 2020-09-05, Croatia
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Computing

Abstract

U ovom radu je dan kratak opis općenitih pristupa klasifikacije i regresije, kao pristupa nadziranog učenja, kao i objašnjenje regresijskih i klasifikacijskih stabala odluke. Dana je analiza algoritma za pojačavanje, gdje su regresijska stabla odluke temeljena na modelu slabog učenika. Takod̄er je objašnjena implementacija naprednog algoritma stabala odluke XGBoost.

Abstract (english)

In this paper a short introduction to classification and regression is given, as well as general explanation of supervised learning approches. In addition, an introduction to regression and classification trees is given. Gradient boosting algorithm for regression trees as weak learners, is analyzed too. Implementation of advanced decision tree algorithm XGBoost is also described.

• Keywords: klasifikacija; regresija; algoritam za pojačavanje; algoritam podizanja gradijenta; xgboost
• Keywords (english): classification; regression; boosting; gradient boosting; xgboost
• Language: croatian
• URN:NBN: urn:nbn:hr:168:987051
• Study programme: Title: Computing; Study programme type: university; Study level: undergraduate; Academic / professional title: sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva (sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Closed access
• Created on: 2023-01-14 09:01:23