Uporaba strojnega učenja za napovedovanje škodnih dogodkov

Čoh, Vito

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Title:	Uporaba strojnega učenja za napovedovanje škodnih dogodkov
Authors:	ID Čoh, Vito (Author) ID Jakovac, Marko (Mentor) More about this mentor... ID Harej, Bor (Comentor)
Files:	MAG_Coh_Vito_2020.pdf (1,53 MB) MD5: 0773758FBFE80558ACCAE8E2E41AFD49 PID: 20.500.12556/dkum/9b55a56d-77eb-46f1-b7c5-12d0f613687b
Language:	Slovenian
Work type:	Master's thesis/paper
Typology:	2.09 - Master's Thesis
Organization:	FNM - Faculty of Natural Sciences and Mathematics
Abstract:	V magistrskem delu je predstavljena uporaba posplošenega linearnega modela in različnih metod strojnega učenja v zavarovalništvu. Delo je razdeljeno na teoretični in praktični del. Na začetku teoretičnega dela so opisani osnovni pojmi iz verjetnosti in zavarovalništva. Predstavljeno je tudi, kako zavarovalnice določijo višino premije. Nato sta predstavljena teoretično ozadje posplošenega linearnega modela in uporaba tega modela za napovedovanje višine škode. Na koncu teoretičnega dela pa je opisano strojno učenje in bolj podrobno so predstavljena odločitvena drevesa, naključni gozdovi ter nevronske mreže. V praktičnem delu magistrskega dela pa so posplošeni linearni model, naključni gozd in nevronska mreža uporabljeni za napovedovanje višine škode pri avtomobilskem zavarovanju. Najprej so podatki predstavljeni ter ustrezno obdelani. Nato so določeni parametri posameznih modelov. Na koncu pa so modeli med seboj primerjani in izbran je najboljši model.
Keywords:	zavarovalništvo, posplošeni linearni model, strojno učenje, odločitveno drevo, naključni gozd, nevronska mreža
Place of publishing:	Maribor
Publisher:	[V. Čoh]
Year of publishing:	2020
PID:	20.500.12556/DKUM-75589
UDC:	519.233:004.85(043.2)
COBISS.SI-ID:	17705219
NUK URN:	URN:SI:UM:DK:JNAVDIPG
Publication date in DKUM:	09.06.2020
Views:	1857
Downloads:	197
Metadata:
Categories:	FNM
:	ČOH, Vito, 2020, Uporaba strojnega učenja za napovedovanje škodnih dogodkov [online]. Master’s thesis. Maribor : V. Čoh. [Accessed 31 March 2025]. Retrieved from: https://dk.um.si/IzpisGradiva.php?lang=eng&id=75589 Copy citation

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Licences

License:	CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International

Link:	http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:	The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:	12.12.2019

Secondary language

Language:	English
Title:	Using machine learning to predict loss events
Abstract:	The master thesis presents the use of generalized linear model and different machine learning methods in insurance. It is divided into theoretical and practical part. At the beginning of the theoretical part, basic notions of probability and insurance are described. It is also presented, how insurance companies determine the insurance premium. Then the theoretical background of generalized linear model and the use of it in predicting claim amount are presented. At the end of the theoretical part, machine learning is described and also decision trees, random forests and neural networks are presented in detail. The practical part of master thesis is focused on how generalized linear model, random forest and neural network are used for predicting car insurance claims. First, the data is presented and processed. Then the parameters of each model are determined. In the end, the models are compared and the best one is chosen.
Keywords:	insurance, generalized linear model, machine learning, decision tree, random forest, neural network

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