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Abstract: Selective induction algorithms are efficient in learning target concepts but inherit a major limitation - each time only one feature is used to partition the data until the data is divided into uniform segments. This limitation results in problems like replication, repetition, and fragmentation. Constructive induction has been an effective means to overcome some of the problems. The underlying idea is to construct compound features that increase the representation power so as to enhance the... (Update)
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BibTeX entry: (Update)
@misc{ and-fragmentation,
author = "Rudy Setiono And",
title = "Fragmentation Problem and Automated Feature Construction",
url = "citeseer.ist.psu.edu/303452.html" }
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