Abstract
By identifying characteristic regions in which classes are dense and also relevant for discrimination a new, intuitive classification method is set up. This method enables a visualized result so the user is provided with an insight into the data with respect to discrimination for an easy interpretation. Additionally, it outperforms Decision trees in a lot of situations and is robust against outliers and missing values. © Springer-Verlag Berlin Heidelberg 2005.
Cite
CITATION STYLE
Szepannek, G., Luebke, K., & Weihs, C. (2005). Understanding patterns with different subspace classification. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3587 LNAI, pp. 110–119). Springer Verlag. https://doi.org/10.1007/11510888_12
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