Abstract
The paper is devoted to the study of a greedy algorithm for construction of approximate decision rules. This algorithm is applicable to decision tables with many-valued decisions where each row is labeled with a set of decisions. For a given row, we should find a decision from the set attached to this row. We consider bounds on the precision of this algorithm relative to the length of rules. To illustrate proposed approach we study a problem of recognition of labels of points in the plain. This paper contains also results of experiments with modified decision tables from UCI Machine Learning Repository.
Original language | English (US) |
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Title of host publication | Lecture Notes in Computer Science |
Publisher | Springer Nature |
Pages | 24-50 |
Number of pages | 27 |
ISBN (Print) | 9783662536100 |
DOIs | |
State | Published - Oct 21 2016 |
Bibliographical note
KAUST Repository Item: Exported on 2020-10-01Acknowledgements: Research reported in this publication was supported by the King Abdullah University of Science and Technology (KAUST). The authors wish to express their gratitude to anonymous reviewers for useful comments.