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Response classification in psychological testing using a neural network.

T Sams·P Laursen·L Eskelinen
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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%.

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HumansNeural Networks, ComputerNeuropsychological TestsLetterResearch Support, Non-U.S. Gov't

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BibTeXRIS

T Sams, P Laursen, L Eskelinen. 1994. Response classification in psychological testing using a neural network.. https://doi.org/10.1142/s0129065794000268

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