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On Complexity of Deterministic and Nondeterministic Decision Trees for Conventional Decision Tables from Closed Classes [PDF]
Entropy, 2023 In this paper, we consider classes of conventional decision tables closed relative to the removal of attributes (columns) and changing decisions assigned to rows.
Azimkhon Ostonov, Mikhail Moshkov
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Decision Trees for Binary Subword-Closed Languages [PDF]
Entropy, 2023 In this paper, we study arbitrary subword-closed languages over the alphabet {0,1} (binary subword-closed languages). For the set of words L(n) of the length n belonging to a binary subword-closed language L, we investigate the depth of the decision ...
Mikhail Moshkov
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Comparative Analysis of Deterministic and Nondeterministic Decision Trees for Decision Tables from Closed Classes [PDF]
EntropyIn this paper, we consider classes of decision tables with many-valued decisions closed under operations of the removal of columns, the changing of decisions, the permutation of columns, and the duplication of columns.
Azimkhon Ostonov, Mikhail Moshkov
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Decision trees: from efficient prediction to responsible AI [PDF]
Frontiers in Artificial Intelligence, 2023 This article provides a birds-eye view on the role of decision trees in machine learning and data science over roughly four decades. It sketches the evolution of decision tree research over the years, describes the broader context in which the research ...
Hendrik Blockeel +6 more
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Applications of Depth Minimization of Decision Trees Containing Hypotheses for Multiple-Value Decision Tables [PDF]
Entropy, 2023 In this research, we consider decision trees that incorporate standard queries with one feature per query as well as hypotheses consisting of all features’ values.
Mohammad Azad, Mikhail Moshkov
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Decision trees in epidemiological research [PDF]
Emerging Themes in Epidemiology, 2017 Background In many studies, it is of interest to identify population subgroups that are relatively homogeneous with respect to an outcome. The nature of these subgroups can provide insight into effect mechanisms and suggest targets for tailored ...
Ashwini Venkatasubramaniam +5 more
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, 2015 In order to speed-up classification models when facing a large number of categories, one usual approach consists in organizing the categories in a particular structure, this structure being then used as a way to speed-up the prediction computation.
Denoyer, Ludovic, Léon, Aurélia
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Data-Driven EEG Band Discovery with Decision Trees [PDF]
Sensors, 2022 Electroencephalography (EEG) is a brain imaging technique in which electrodes are placed on the scalp. EEG signals are commonly decomposed into frequency bands called delta, theta, alpha, and beta.
Shawhin Talebi +4 more
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A Review and Experimental Comparison of Multivariate Decision Trees
IEEE Access, 2021 Decision trees are popular as stand-alone classifiers or as base learners in ensemble classifiers. Mostly, this is due to decision trees having the advantage of being easy to explain.
Leonardo Canete-Sifuentes +2 more
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