Minimization of Decision Tree Average Depth for Decision Tables with Many-valued Decisions | Zendy

Mohammad Azad | Zendy; Mikhail Moshkov | Zendy

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Minimization of Decision Tree Average Depth for Decision Tables with Many-valued Decisions

Author(s) -

Mohammad Azad,

Mikhail Moshkov

Publication year - 2014

Publication title -

procedia computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.334

H-Index - 76

ISSN - 1877-0509

DOI - 10.1016/j.procs.2014.08.117

Subject(s) - computer science , decision tree , minification , optimal decision , greedy algorithm , set (abstract data type) , mathematical optimization , dynamic programming , decision table , algorithm , mathematics , artificial intelligence , rough set , programming language

The paper is devoted to the analysis of greedy algorithms for the minimization of average depth of decision trees for decision tables such that each row is labeled with a set of decisions. The goal is to find one decision from the set of decisions. When we compare with the optimal result obtained from dynamic programming algorithm, we found some greedy algorithms produces results which are close to the optimal result for the minimization of average depth of decision trees

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