Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06)
Decision Tree Construction from Multidimensional Structured Data
Hong Kong, China
December 18-December 22
ISBN: 0-7695-2702-7
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.
Citation:
Tomoki Watanuma, Tomonobu Ozaki, Takenao Ohkawa, "Decision Tree Construction from Multidimensional Structured Data," icdmw, pp.237-241, Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06), 2006