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Lower Bounds on Complexity of Deterministic Decision Trees for Decision Tables
Intelligent Systems Reference Library, 2020In this chapter, lower bounds on complexity of deterministic decision trees for decision tables are studied that are based on the notions of super-cover, super-partition, test, and system of representatives for decision tables. An approach to the proof of lower bounds is also considered which is based on the use of so-called proof-trees.
Mikhail Moshkov
exaly +3 more sources
Time and Space Complexity of Deterministic and Nondeterministic Decision Trees: Local Approach
2023 IEEE International Conference on Big Data (BigData), 2023Extensive research has been conducted on rough set theory, specifically focusing on the study of decision trees (DTs) and decision rule systems (DRSs).
Mikhail Moshkov, Kerven Durdymyradov
exaly +4 more sources
Intelligent Systems Reference Library, 2020
In this chapter, upper bounds on the minimum complexity and algorithms for construction of deterministic decision trees for decision tables are considered. These bounds and algorithms are based on the use of so-called additive-bounded uncertainty measures for decision tables.
Mikhail Moshkov
exaly +3 more sources
In this chapter, upper bounds on the minimum complexity and algorithms for construction of deterministic decision trees for decision tables are considered. These bounds and algorithms are based on the use of so-called additive-bounded uncertainty measures for decision tables.
Mikhail Moshkov
exaly +3 more sources
Deterministic and Nondeterministic Decision Trees for Recognition of All Realizable Decision Rules
Lecture Notes in Computer ScienceMikhail Moshkov, Kerven Durdymyradov
exaly +4 more sources
Deterministic and Nondeterministic Decision Trees for Rough Computing
Fundamenta Informaticae, 2000In the paper, infinite information systems are considered which are used in pattern recognition, discrete optimization, computational geometry. Depth and size of deterministic and nondeterministic decision trees over such information systems are studied. Two classes of infinite information systems are investigated.
M. Moshkov
semanticscholar +4 more sources
Decision Support Using Deterministic Equivalents of Probabilistic Game Trees
2012 IEEE 19th International Conference and Workshops on Engineering of Computer-Based Systems, 2012We have developed a game-theory driven decision-support tool that builds probabilistic game trees automatically from user-defined actions, rules, and states. The result of evaluating the paths in the game tree is a series of decisions which forms a decision-path representing an epsilon-Nash-Equilibrium.
Michael L. Valenzuela +2 more
semanticscholar +3 more sources
, 2020
In this chapter, for complexity functions having the properties \(\varLambda 1 \), \(\varLambda 2\), and \(\varLambda 3\), upper bounds on the minimum complexity and algorithms for construction of deterministic decision trees for decision tables are considered. These bounds and algorithms are based on the use of so-called difference-bounded uncertainty
M. Moshkov
semanticscholar +2 more sources
In this chapter, for complexity functions having the properties \(\varLambda 1 \), \(\varLambda 2\), and \(\varLambda 3\), upper bounds on the minimum complexity and algorithms for construction of deterministic decision trees for decision tables are considered. These bounds and algorithms are based on the use of so-called difference-bounded uncertainty
M. Moshkov
semanticscholar +2 more sources
Deterministic and Nondeterministic Decision Trees for Decision Rule Systems from Closed Classes
Lecture Notes in Computer ScienceMikhail Moshkov, Kerven Durdymyradov
exaly +2 more sources