ACMD: A Practical Tool for Automatic Neural Net Based Learning

Roland Linder, Siegfried J. Pöppl


Although neural networks have many appealing properties, yet there is neither a systematic way how to set up the topology of a neural network nor how to determine its various learning parameters. Thus an expert is needed for fine tuning. If neural network applications should not be realisable only for publications but in real life, fine tuning must become unnecessary. We developed a tool called ACMD (Approximation and Classification of Medical Data) that is demonstrated to fulfil this demand. Moreover referring to six medical classification and approximation problems of the PROBEN1 benchmark collection this approach will be shown even to outperform fine tuned networks.

Original languageEnglish
Title of host publicationISMDA 2001: Medical Data Analysis
Number of pages6
PublisherSpringer Berlin Heidelberg
Publication date01.01.2001
ISBN (Print)978-3-540-42734-6
ISBN (Electronic)978-3-540-45497-7
Publication statusPublished - 01.01.2001
Event2nd International Symposium on Medical Data Analysis
- Madrid, Spain
Duration: 08.10.200109.10.2001
Conference number: 120889


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