Optimization of model points

dc.contributor.advisorPärna, Kalev, juhendaja
dc.contributor.authorCuevas Urosa, Miguel
dc.contributor.otherTartu Ülikool. Matemaatika-informaatikateaduskondet
dc.contributor.otherTartu Ülikool. Matemaatilise statistika instituutet
dc.date.accessioned2014-07-11T09:51:33Z
dc.date.available2014-07-11T09:51:33Z
dc.date.issued2014-06-18
dc.description.abstractThe aim of this work is to study the Nonnegative Least Squares Optimization, to investigate if it is possible to reduce the number of model points in a dataset to save time. We will start with a huge dataset from an insurance company, we are going to optimize this dataset and reduce the number of model point without losing significant accuracy. We do this with the Nonnegative Least Squares (NNLS) method. In this thesis, NNLS will be described briefly, results and conclusions from the NNLS optimization are shown and discussed.et
dc.identifier.urihttp://hdl.handle.net/10062/42548
dc.language.isoenet
dc.publisherTartu Ülikoolet
dc.subjectmittenegatiivne vähimruutude meetodet
dc.subjectmudelpunktidet
dc.subjectelukindlustuset
dc.subject.othermagistritöödet
dc.subject.othernon-negative least squaresen
dc.subject.othermodel pointsen
dc.subject.otherlife insuranceen
dc.titleOptimization of model pointset
dc.typeThesiset

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