Pattern Classification

Backpropagation as Feature MappingInput layer to hidden layer weights for a character recognition taskWeights at two hidden nodesrepresented as 8x8 patternsLeft gets activated for F, right getsactivated for L, and both getactivated for E• 64-2-3 sigmoidal network for classifying three characters (E,F,L)• Non-linear interactions between the features may cause thefeatures of the pattern to not manifest in a single hidden node (incontrary to the example shown above)• It may be difficult to draw similar interpretations in large networksand caution must be exercised while analyzing weights