Uncertainty in decision tree classifiers

Authors:
Matteo Magnani;Danilo Montesi
Affiliations:
Dept. of Computer Science, University of Bologna, Bologna;Dept. of Computer Science, University of Bologna, Bologna
Venue:
SUM'10 Proceedings of the 4th international conference on Scalable uncertainty management
Year:
2010

Citing 9
Cited 0

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Abstract

One of the current challenges in the field of data mining is to develop techniques to analyze uncertain data. Among these techniques, in this paper we focus on decision tree classifiers. In particular, we introduce a new data structure that can be used to represent multiple decision trees generated from uncertain datasets.