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Your query term was 'number = 92-15'1 report found
- ÖFAI-TR-92-15
Reanalyzing Similarity Measures in Neural Networks and Their Practical Consequences
- Georg Dorffner, Herbert Wiklicky
- Neural networks are said to treat inputs sensitively to their
similarities. Therefore, success of a neural network application
depends on whether the ``right'' similarities are recognized. We
argue that, although some theory exists, many practical applications
have neglected some, often surprising, limits based on the similarity
measures employed by the networks. We then reanalyze some common
measures from a practical point of view, revealing some of those
limits, including a paradox of patterns that are ``more similar''
than the desired prototypes. We conclude this paper with a list of
heuristics for network design and argue for a fruitful
cross-fertilization of neural network subfields.
Keywords: , Neural Networks, Similarity Measures, Practical, Applications, Performance Analysis
- Neural networks are said to treat inputs sensitively to their
similarities. Therefore, success of a neural network application
depends on whether the ``right'' similarities are recognized. We
argue that, although some theory exists, many practical applications
have neglected some, often surprising, limits based on the similarity
measures employed by the networks. We then reanalyze some common
measures from a practical point of view, revealing some of those
limits, including a paradox of patterns that are ``more similar''
than the desired prototypes. We conclude this paper with a list of
heuristics for network design and argue for a fruitful
cross-fertilization of neural network subfields.