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PAKDD
2004
ACM

A Metric Approach to Building Decision Trees Based on Goodman-Kruskal Association Index

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A Metric Approach to Building Decision Trees Based on Goodman-Kruskal Association Index
We introduce a numerical measure on sets of partitions of finite sets that is linked to the Goodman-Kruskal association index commonly used in statistics. This measure allows us to define a metric on such partions used for constructing decision trees. Experimental results suggest that by replacing the usual splitting criterion used in C4.5 by a metric criterion based on the Goodman-Kruskal coefficient it is possible, in most cases, to obtain smaller decision trees without sacrificing accuracy.
Dan A. Simovici, Szymon Jaroszewicz
Added 02 Jul 2010
Updated 02 Jul 2010
Type Conference
Year 2004
Where PAKDD
Authors Dan A. Simovici, Szymon Jaroszewicz
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