Knowledge pruning in decision trees

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12th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'00)

Vancouver, British Columbia, Canada

November 13-November 15

ISBN: 0-7695-0909-6

	ASCII Text	x
	I. Shioya, T. Miura, "Knowledge pruning in decision trees," Tools with Artificial Intelligence, IEEE International Conference on, pp. 0040, 12th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'00), 2000.

	BibTex	x
	@article{ 10.1109/TAI.2000.889844, author = {I. Shioya and T. Miura}, title = {Knowledge pruning in decision trees}, journal ={Tools with Artificial Intelligence, IEEE International Conference on}, volume = {0}, year = {2000}, isbn = {0-7695-0909-6}, pages = {0040}, doi = {http://doi.ieeecomputersociety.org/10.1109/TAI.2000.889844}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Tools with Artificial Intelligence, IEEE International Conference on TI - Knowledge pruning in decision trees SN - 0-7695-0909-6 SP EP A1 - I. Shioya, A1 - T. Miura, PY - 2000 KW - decision trees; learning (artificial intelligence); data mining; knowledge pruning; decision trees; pruning method; domain knowledge; semantic hierarchies; hierarchy levels; UCI Machine Learning Repository On Car Evaluation and Nursery VL - 0 JA - Tools with Artificial Intelligence, IEEE International Conference on ER -

I. Shioya, Sanno Univ., Kanagawa, Japan

T. Miura, Sanno Univ., Kanagawa, Japan

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TAI.2000.889844

Abstract: We propose a novel pruning method of decision trees based on domain knowledge, semantic hierarchies among classes, which is used to generate decision trees by relaxing the levels of hierarchies for both height and width of the trees. We develop the algorithm, and the effectiveness is examined by UCI Machine Learning Repository: On Car Evaluation and Nursery. We can generate the decision trees consisting of 11 and 13 rules, although C4.5 generates 182 and 572 rules, respectively.

Index Terms:

decision trees; learning (artificial intelligence); data mining; knowledge pruning; decision trees; pruning method; domain knowledge; semantic hierarchies; hierarchy levels; UCI Machine Learning Repository On Car Evaluation and Nursery

Citation:

I. Shioya, T. Miura, "Knowledge pruning in decision trees," ictai, pp.0040, 12th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'00), 2000

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