Results 231 to 240 of about 86,158 (257)

Comparative Analysis of Deterministic and Nondeterministic Decision Tree Complexity Local Approach

Fundamenta Informaticae, 2005
We study the relationships between the complexity of a task description and the minimal complexity of deterministic and nondeterministic decision trees solving this task. We investigate decision trees assuming a global approach i.e. arbitrary checks from a given check system can be used for constructing decision trees.
Mikhail Moshkov
openalex   +3 more sources

Decision Support Using Deterministic Equivalents of Probabilistic Game Trees

2012 IEEE 19th International Conference and Workshops on Engineering of Computer-Based Systems, 2012
We 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, Liana Suantak, Jerzy W. Rozenblit   +2 more
openalex   +2 more sources

Development of Converted Deterministic Finite Automaton of Decision Tree Rules of Student Graduation and Adaptive Learning Environment

Proceedings of the 6th International Conference on Information Technology: IoT and Smart City, 2018
In theory of computation, a deterministic finite automaton (DFA) is a finite state machine that accepts/rejects finite strings of symbols and only produces a unique computation. This study aims to convert the extracted decision tree rules sets from decision tree algorithm and the learning path sequence of the learning management system.
Ace C. Lagman, Melvin A. Ballera, Jennifer Contreras, Jennalyn G. Raviz   +3 more
openalex   +2 more sources

Upper Bounds on Complexity and Algorithms for Construction of Deterministic Decision Trees for Decision Tables. First Approach

, 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
Mikhail Moshkov
openalex   +2 more sources

Conversion of Decision Tree Into Deterministic Finite Automaton for High Accuracy Online SYN Flood Detection

2015 IEEE Symposium Series on Computational Intelligence, 2015
While collecting data from network traffic, one can create classifiers that recognize threats, anomalies, or other events. The set of labelled Net Flow records collecting traffic statistics is a very useful source of decision rules that classify the records. These rules can be created automatically using machine learning techniques.
Marcin Luckner
openalex   +2 more sources

Time and Space Complexity of Deterministic and Nondeterministic Decision Trees: Local Approach

2023 IEEE International Conference on Big Data (BigData), 2023
Kerven Durdymyradov, Mikhail Moshkov
openalex   +2 more sources

Decision Trees: Sensitivity Analysis, Deterministic

, 2009
Michael W. Kattan
openalex   +2 more sources

Deterministic and Nondeterministic Decision Trees for Decision Tables with Many-Valued Decisions from Closed Classes

, 2023
Azimkhon Ostonov, Mikhail Moshkov
openalex   +2 more sources

Comparative Analysis of Deterministic and Nondeterministic Decision Tree Complexity. Global Approach

Kerven Durdymyradov, Mikhail Moshkov, Azimkhon Ostonov   +2 more
openalex   +2 more sources

Deterministic and Nondeterministic Decision Trees for Recognition of All Realizable Decision Rules

Kerven Durdymyradov, Mikhail Moshkov
openalex   +2 more sources