Abstract
This paper analyzes two different approaches to the detection of supporting factors used in descriptive induction. The first is based on the statistical comparison of the pattern properties relative to the properties of the entire negative and the entire positive example sets. The other approach uses artificially generated random examples that are added into the original training set. The methodology is illustrated in the analysis of patients suffering from brain ischaemia.
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© 2007 Springer-Verlag Berlin Heidelberg
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Gamberger, D., Lavrač, N. (2007). Supporting Factors in Descriptive Analysis of Brain Ischaemia. In: Bellazzi, R., Abu-Hanna, A., Hunter, J. (eds) Artificial Intelligence in Medicine. AIME 2007. Lecture Notes in Computer Science(), vol 4594. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73599-1_18
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DOI: https://doi.org/10.1007/978-3-540-73599-1_18
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-73598-4
Online ISBN: 978-3-540-73599-1
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