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Imputing missing values for mixed-type tabular datasets using generative adversarial networks

dc.rights.licenseCC-BY-NC-ND
dc.contributor.advisorQahtan, Hakim
dc.contributor.authorBannany, Ouassim
dc.date.accessioned2022-09-09T00:01:12Z
dc.date.available2022-09-09T00:01:12Z
dc.date.issued2022
dc.identifier.urihttps://studenttheses.uu.nl/handle/20.500.12932/42359
dc.description.sponsorshipUtrecht University
dc.language.isoEN
dc.subjectIn this thesis a framework has been introduced based on generative adversarial networks to impute any missing value in the data set. This complete data can then be used for further analysis, or to train predictive models.
dc.titleImputing missing values for mixed-type tabular datasets using generative adversarial networks
dc.type.contentMaster Thesis
dc.rights.accessrightsOpen Access
dc.subject.courseuuApplied Data Science
dc.thesis.id6890


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