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2013 IEEE 13th International Conference on Data Mining Workshops (2006)
Hong Kong, China
Dec. 18, 2006 to Dec. 22, 2006
ISBN: 0-7695-2702-7
pp: 237-241
Takenao Ohkawa , Kobe University
Tomoki Watanuma , Kobe University
Tomonobu Ozaki , Kobe University
ABSTRACT
Since most structured data mining techniques specialize in mining from single structured data, it cannot handle more realistic data which consist of different and plural kinds of structured data. To cope with this problem, we propose an algorithm for constructing decision trees from multidimensional structured data by introducing the techniques for mining correlated and closed patterns with effective pruning capabilities into the traditional TDIDT approach. The results of the experiments with real world data show the effectiveness of the proposed algorithm.
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CITATION
Takenao Ohkawa, Tomoki Watanuma, Tomonobu Ozaki, "Decision Tree Construction from Multidimensional Structured Data", 2013 IEEE 13th International Conference on Data Mining Workshops, vol. 00, no. , pp. 237-241, 2006, doi:10.1109/ICDMW.2006.57
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