Predicting Gas-Particle Partitioning Properties of Atmospheric Molecules Using Kernel Ridge Regression

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dc.contributorAalto-yliopistofi
dc.contributorAalto Universityen
dc.contributor.advisorTodorovic, Milica
dc.contributor.authorLumiaro, Emma
dc.contributor.schoolPerustieteiden korkeakoulufi
dc.contributor.supervisorRinke, Patrick
dc.date.accessioned2019-12-24T10:11:03Z
dc.date.available2019-12-24T10:11:03Z
dc.date.issued2019-12-11
dc.format.extent29
dc.format.mimetypeapplication/pdfen
dc.identifier.urihttps://aaltodoc.aalto.fi/handle/123456789/41782
dc.identifier.urnURN:NBN:fi:aalto-201912246731
dc.language.isoenen
dc.programmeTeknistieteellinen kandidaattiohjelmafi
dc.programme.majorTeknillinen fysiikkafi
dc.programme.mcodeSCI3028fi
dc.subject.keywordmachine learningen
dc.subject.keywordkernel ridge regressionen
dc.subject.keywordaerosolsen
dc.titlePredicting Gas-Particle Partitioning Properties of Atmospheric Molecules Using Kernel Ridge Regressionen
dc.typeG1 Kandidaatintyöfi
dc.type.dcmitypetexten
dc.type.ontasotBachelor's thesisen
dc.type.ontasotKandidaatintyöfi

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