Usporedba metoda grupiranja i modela predviđanja za prostorne podatke

master's thesis

• Title (english): A Comparison of Clustering Methods and Prediction Models for Spatial Data
• Author: Ivo Karamatić
• Mentor: Krešimir Pripužić (mentor)
• Committee member: Krešimir Pripužić (predsjednik povjerenstva)
• Committee member: Marin Vuković (član povjerenstva)
• Committee member: Dragan Jevtić (član povjerenstva)
• Granter: University of Zagreb; Faculty of Electrical Engineering and Computing; Zagreb
• Defense date and country: 2022-07-12, Croatia
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Computing

Abstract

U ovom je radu dana usporedba kombinacija različitih metoda grupiranja i modela predviđanja provedena nad prostornim podacima. Teorijski su opisane sve korištene metode grupiranja, kao i korišteni modeli predviđanja. Osim njih, objašnjene su metrike korištene za evaluaciju metoda grupiranja i metrike korištene za evaluaciju modela predviđanja. Zatim su opisani korišteni skup podataka i korišteni programski alati. Konačno, na samom kraju rada dan je pregled rezultata provedene usporedbe.

Abstract (english)

The main goal of this thesis was to compare the performance of different combinations of clustering methods and prediction models for spatial data. Every clustering method that ended up in the practical implementation, as well as every prediction model, was described in the theoretical part of the thesis. Metrics used to evaluate clustering methods and prediction models were described as well. Furthermore, the thesis contains details about the dataset, tools and software libraries necessary for the practical implementation. Finally, the last part of this thesis gives an overview of the obtained results.

• Keywords: usporedba; grupiranje; predviđanje; predikcija; regresija; prostorni podaci; Python; algoritam K-sredina; model Gaussove mješavine; aglomerativno hijerarhijsko grupiranje; algoritam BIRCH; linearna regresija; robusna regresija; bayesovska hrbatna regresija; stroj potpornih vektora; algoritam slučajnih šuma
• Keywords (english): comparison; clustering; prediction; regression; spatial data; Python; Kmeans; Gaussian mixture; Agglomerative hierarchical clustering; BIRCH; linear regression; robust regression; Bayesian ridge regression; support vector machine; random forest
• Language: croatian
• URN:NBN: urn:nbn:hr:168:175534
• 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: 2023-01-14 09:04:26