Napredni algoritmi stabala odluke

undergraduate thesis

• Title (english): Decision Trees
• Author: Ante Prpić
• Mentor: Vladimir Čeperić (mentor)
• Committee member: Vladimir Čeperić (predsjednik povjerenstva)
• Committee member: Igor Stančin (član povjerenstva)
• Committee member: Ivan Grubišić (član povjerenstva)
• Granter: University of Zagreb; Faculty of Electrical Engineering and Computing; Zagreb
• Defense date and country: 2019-09-17, Croatia
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Computing

Abstract

Upoznavanje s problemima strojnog učenja rješivim implementacijama naprednim
algoritmima stabala odluka, poput pojačivačke biblioteke XGBoost koja na temelju
procjena slabih modela donosi zaključke uzimajući u obzir bitne značajke skupa
podataka gradeći dobar model koji precizno rješava probleme klasifikacije i
regresije.

Abstract (english)

An overview of advanced decision trees boosting algorithms like XGBoost used for
solving machine learning problems like classification and regression combining
sets of weak classifiers while trying to build an improved, strong model
that precisely addresses classification and regression problems.

• Keywords: stabla odluke; xgboost; regresija; klasifikacija; pojačavanje; nadzirano učenje
• Keywords (english): decision tree; xgboost; regression; classification; boosting; supervised learning; time series
• Language: croatian
• URN:NBN: urn:nbn:hr:168:558281
• 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: 2020-01-07 21:36:48