Investigating the reliability of a low-back-pain MLP by using a full explanation facility

This study investigates the reliability of a low-back-pain multilayer perceptron network from a hidden layer decision region perspective. Using decision region information from an explanation facility the training examples are discovered to occupy decision regions in contiguous class threads across...

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Bibliographic Details
Published inIJCNN'01. International Joint Conference on Neural Networks. Proceedings (Cat. No.01CH37222) Vol. 4; pp. 2683 - 2688 vol.4
Main Authors Vaughn, M.L., Taylor, S.J., Foy, M.A., Fogg, A.J.B.
Format Conference Proceeding
LanguageEnglish
Published IEEE 2001
Subjects
Binary codes
Hospitals
Multilayer perceptrons
Neurons
Orthopedic surgery
Pain
Standards development
Testing
Training data
Yarn
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Summary:This study investigates the reliability of a low-back-pain multilayer perceptron network from a hidden layer decision region perspective. Using decision region information from an explanation facility the training examples are discovered to occupy decision regions in contiguous class threads across the 48-dimensional input space. Test cases show a similar distribution and consistency within the contiguous threads but with a reduced reliability. Three test regions outside the network's knowledge bounds are situated between training regions with a consistent classification. The hypothesis that classifications are reliable within the knowledge bounds and potentially unreliable outside the knowledge bounds is examined.
ISBN:0780370449
9780780370449
ISSN:1098-7576
1558-3902
DOI:10.1109/IJCNN.2001.938794