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Abstract: : The main problem considered in this paper consists of binarizing categorical (nominal) attributes having a very large number of values (20 4 in our application). Few number of relevant binary attributes are gathered from each initial attribute. The signiøcant idea consists in grouping the values of an attribute by means of an hierarchical classiøcation method. The similarity between values is associated with the classes to be predicted. The solution that we propose is independant of the... (Update)
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BibTeX entry: (Update)
@misc{ el-c'esar-reducing,
author = "Isra El-C'esar",
title = "Reducing the number of binary splits, in Decision Tree Induction, by means
of an Hierarchical Classification",
url = "citeseer.ist.psu.edu/61415.html" }
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