Greedy Algorithm for the Construction of Approximate Decision Rules for Decision Tables with Many-Valued Decisions
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AbstractThe 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.
CitationAzad M, Moshkov M, Zielosko B (2016) Greedy Algorithm for the Construction of Approximate Decision Rules for Decision Tables with Many-Valued Decisions. Lecture Notes in Computer Science: 24–50. Available: http://dx.doi.org/10.1007/978-3-662-53611-7_2.
SponsorsResearch 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.