Investigating the reliability of a low-back-pain MLP by using a full explanation facility
M.L. Vaughn, Stewart J. Taylor, Michael A. Foy, Anthony J. B. Fogg · 2002
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.