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Modelling rare events using non-parametric machine learning classifiers - Under what circumstances are support vector machines preferable to conventional parametric classifiers?


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Title: Modelling rare events using non-parametric machine learning classifiers - Under what circumstances are support vector machines preferable to conventional parametric classifiers?
Other Titles: Modellering av ”rare events” med hjälp av maskininlärningsmetoder -- under vilka omständigheter är det mer lämpligt att tillämpa SVM än de konventionella klassificeringsmetoderna?
Authors: Ma, Lukas
Issue Date: 6-Apr-2021
Degree: Student essay
Series/Report no.: 202104:61
Uppsats
Abstract: Rare event modelling is an important topic in quantitative social science research. However, despite the fact that traditional classifiers based upon general linear models (GLM) might lead to biased results, little attention in the social science community is devoted to methodological studies aimed at alleviating such bias, even fewer of them have considered the use of machine learning methods to tackle analytical problems imposed by rare events. In this thesis, I compared the classification perf... more
URI: http://hdl.handle.net/2077/68195
Appears in Collections:Kandidatuppsatser / Institutionen för nationalekonomi och statistik

 

 

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