Results 11 to 20 of about 3,608,849 (131)
A Local Approach to Studying the Time and Space Complexity of Deterministic and Nondeterministic Decision Trees [PDF]
CoRR, 2023 In this paper, we study arbitrary infinite binary information systems each of which consists of an infinite set called universe and an infinite set of two-valued functions (attributes) defined on the universe.
Moshkov, Mikhail, Durdymyradov, Kerven
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Comparison of Deterministic and Nondeterministic Decision Trees for Decision Tables with Many-valued Decisions from Closed Classes [PDF]
CoRR, 2023 In this paper, we consider classes of decision tables with many-valued decisions closed relative to removal of attributes (columns) and changing sets of decisions assigned to rows.
Moshkov, Mikhail, Ostonov, Azimkhon
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Procedia Computer ScienceDecision rule systems and decision trees are frequently used in computer science as interpretable models. Understanding their complexity in terms of attribute costs is crucial when decisions must be made with minimum resource usage.
Moshkov, Mikhail, Durdymyradov, Kerven
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Time and Space Complexity of Deterministic and Nondeterministic Decision Trees: Local Approach
2023 IEEE International Conference on Big Data (BigData), 2023 Extensive research has been conducted on rough set theory, specifically focusing on the study of decision trees (DTs) and decision rule systems (DRSs).
Moshkov, Mikhail, Durdymyradov, Kerven
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Procedia Computer ScienceThe study of the relationships between decision rule systems and decision trees is of considerable interest in computer science. These models are among the most interpretable tools used in knowledge representation, classification, and decision-making. In
Moshkov, Mikhail, Durdymyradov, Kerven
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This paper examines types of decision tables with many-valued decisions that are closed under the attribute (columns) removal and changes in the sets of decisions assigned to rows.
Moshkov, Mikhail, Ostonov, Azimkhon
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Decision trees (DTRs) and decision rules are extensively examined and applied in various domains of computer science. The theory of DTRs and rules highlights several crucial inquiries, such as how the complexity of deterministic decision trees (DDTRs ...
Moshkov, Mikhail, Ostonov, Azimkhon
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Deterministic and Strongly Nondeterministic Decision Trees for Decision Tables from Closed Classes
CoRR, 2023 In this paper, we consider classes of decision tables with 0-1-decisions closed relative to removal of attributes (columns) and changing decisions assigned to rows. For tables from an arbitrary closed class, we study the dependence of the minimum complexity of deterministic decision trees on various parameters of the tables: the minimum complexity of a
Azimkhon Ostonov, Mikhail Moshkov
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MR Derived Cardiac Metabolism Changes in Patients With Obesity and Diabetes: Knowledge Discovery Via Bayesian Networks and Random Forest Classification [PDF]
NMR BiomedCharacterization of healthy vs. diabetic (73:67$$ 73:67 $$) random forest classification group and its Bayesian network learned through NOTEARS structure algorithm on multi‐modal data. Shown computed SHapley Additive exPlanation (SHAP) values for various features.
Hanninger I +8 more
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Comparative Analysis of Deterministic and Nondeterministic Decision Trees for Decision Tables from Closed Classes [PDF]
, 2023 In this paper, we consider classes of decision tables with many-valued decisions closed under operations of removal of columns, changing of decisions, permutation of columns, and duplication of columns.
Moshkov, Mikhail, Ostonov, Azimkhon
core