Preprocessing perceptrons and multivariate reference values
2009 (English)In: Data mining and medical knowledge management: cases and applications / [ed] Petra Berka, Jan Rauch, and Djamel Abdelkader Zighed, Medical Information Science Reference , 2009, 108-121 p.Chapter in book (Other academic)
Classification networks, consisting of preprocessing layers combined with well-known classification networks, are well suited for medical data analysis. Additionally, by adjusting network complexity to corresponding complexity of data, the parameters in the preprocessing network can, in comparison with networks of higher complexity, be more precisely understood and also effectively utilised as decision limits. Further, a multivariate approach to preprocessing is shown in many cases to increase correctness rates in classification tasks. Handling network complexity in this way thus leads to efficient parameter estimations as well as useful parameter interpretations.
Place, publisher, year, edition, pages
Medical Information Science Reference , 2009. 108-121 p.
IdentifiersURN: urn:nbn:se:umu:diva-34617DOI: 10.4018/978-1-60566-218-3.ch005ISBN: 9781605662183,1605662186, e-issn: 9781605662190OAI: oai:DiVA.org:umu-34617DiVA: diva2:323187