Abstract
In the paper a greedy algorithm for minimization of decision tree depth is described and bounds on the algorithm precision are considered. This algorithm is adapted for application to data tables with both discrete and continuous variables, which can have missing values. To this end we transform given data table into a decision table. Under some natural assumption on the class NP the considered algorithm is close to unimprovable approximate polynomial algorithms for minimization of decision tree depth.
Original language | English (US) |
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Title of host publication | Rough Sets, Fuzzy Sets, Data Mining and Granular Computing - 9th International Conference, RSFDGrC 2003, Proceedings |
Editors | Guoyin Wang, Qing Liu, Yiyu Yao, Andrzej Skowron |
Publisher | Springer Verlag |
Pages | 611-614 |
Number of pages | 4 |
ISBN (Print) | 3540140409, 9783540140405 |
DOIs | |
State | Published - 2003 |
Externally published | Yes |
Event | 9th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing, RSFDGrC 2003 - Chongqing, China Duration: May 26 2003 → May 29 2003 |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 2639 |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Other
Other | 9th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing, RSFDGrC 2003 |
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Country/Territory | China |
City | Chongqing |
Period | 05/26/03 → 05/29/03 |
Bibliographical note
Publisher Copyright:© Springer-Verlag Berlin Heidelberg 2003.
Keywords
- Data table
- Decision table
- Decision tree
- Depth
ASJC Scopus subject areas
- Theoretical Computer Science
- General Computer Science