Response classication in psychological testing using a neural network

T Sams, P A Laursen, L Eskelinen

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

A feedforward neural network with error backpropagation has been designed to recognize hand-drawn patterns in a cognitive test. The architecture uses both position and direction sensitivity in the input layer. The training set consisted of 659 icons which were shifted horizontally and vertically to give a total training set of 5931 icons. In testing on an independent set of 31,192 icons produced by 557 subjects from a Danish standard population sample, the rate of misclassification was 0.12% compared with an average rate of sequence errors of 1.6%.
Original languageEnglish
JournalInternational Journal of Neural Systems
Volume5
Issue number3
Pages (from-to)253-256
ISSN0129-0657
DOIs
Publication statusPublished - 1994
Externally publishedYes

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