Results 41 to 50 of about 3,823,341 (178)
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
A Recursive IndetermTree Soft Set (RIT-Soft Set) for Dynamic and Uncertain Performance Evaluation in College Competitive Sports, [PDF]
Neutrosophic Sets and SystemsThis paper introduces the Recursive IndetermTree Soft Set (RIT-Soft Set), a novel extension of Soft Set Theory designed for performance evaluation in dynamic and uncertain environments.
Hai Yang, Cuijuan Lin
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Conditional Counter-Inspection with Curriculum-Biased Experts for Lightweight 5G Intrusion Detection
Future InternetIn contemporary 5G network environments, intrusion detection systems must balance detection accuracy with operational efficiency, as improvements in one dimension are often achieved at the expense of the other.
Khaoula Tahori +2 more
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, 2008 The inductive learning methodology known as decision trees, concerns the ability to classify objects based on their attributes values, using a tree like structure from which decision rules can be accrued.
Beynon, Malcolm James, Malcolm J. Beynon
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Non-deterministic graph searching in trees [PDF]
, 2015 International audienceNon-deterministic graph searching was introduced by Fomin et al. to provide a unified approach for pathwidth, treewidth, and their interpretations in terms of graph searching games. Given q ≥ 0, the q-limited search number, s q (G),
Amini, Omid +2 more
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MathematicsTreeensembles usually evaluate every tree or boosting stage for every input, even when the partial prediction has already stabilized. We study inference-time lazy evaluation for pre-trained random forests and gradient-boosted decision trees. LazyRF stops
Sooyoung Jang, Sungpil Woo, Ahyun Lee
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More Interpretable Decision Trees
, 2021 We present a new Decision Tree Classifier (DTC) induction algorithm that produces vastly more interpretable trees in many situations. These understandable trees are highly relevant for explainable artificial intelligence, fair automatic classification ...
René Hexel +5 more
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A mass assignment based ID3 algorithm for decision tree induction [PDF]
, 1997 A mass assignment based ID3 algorithm for learning probabilistic fuzzy decision trees is introduced. Fuzzy partitions are used to discretize continuous feature universes and to reduce complexity when universes are discrete but with large cardinalities ...
Baldwin, JF, Martin, TP, Lawry, J
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optRF: Optimising random forest stability by determining the optimal number of trees
BMC BioinformaticsMachine learning is frequently used to make decisions based on big data. Among these techniques, random forest is particularly prominent. Although random forest is known to have many advantages, one aspect that is often overseen is that it is a non ...
Thomas M. Lange +3 more
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Randomized vs. deterministic decision tree complexity for read-once Boolean functions [PDF]
Computational Complexity, 1991 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Rafi Heiman, Avi Wigderson
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