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dc.rights.licenseCC-BY-NC-ND
dc.contributor.advisorHofstee, L.
dc.contributor.advisorBagheri, A.
dc.contributor.authorVerberg, G.
dc.date.accessioned2021-08-25T18:00:13Z
dc.date.available2021-08-25T18:00:13Z
dc.date.issued2021
dc.identifier.urihttps://studenttheses.uu.nl/handle/20.500.12932/41185
dc.description.abstractIt is generally assumed that having more data available will lead to increased performance when using machine learning. This assumption was tested in a specific problem setting: using neural networks in combination with active learning to aid in systematic reviewing. This repository contains the scripts for performing a simulation study using the neural network clasifier as implemented in ASReview. The simulation mode was applied to different sized samples out of three different datasets, to measure the change in performance.
dc.description.sponsorshipUtrecht University
dc.format.extent416072
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.titleThe effect of dataset size on neural network performance within systematic reviewing
dc.type.contentMaster Thesis
dc.rights.accessrightsOpen Access
dc.subject.keywordsNeural Networks, Active Learning, Systematic Reviewing, ASReview
dc.subject.courseuuApplied Data Science


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