作者: Ewa Krusińska , Jerzy Stefanowski , Jan-Erik Strömberg
DOI: 10.1007/978-3-642-51175-2_75
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摘要: In the present paper three different approaches to classification of objects between several a priori known, distinct classes are compared. These are: rough sets, DISQUAL method as well and regression trees (CART). A common set medical data forms basis for comparison. AU methods allow mixture continuous discrete attributes on input via discretization ones. The latter is done automatically in CART but should be given two others. Thus sensitivity changes also studied.