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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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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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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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Induction of decision trees [PDF]
Machine Learning, 1986 The technology for building knowledge-based systems by inductive inference from examples has been demonstrated successfully in several practical applications. This paper summarizes an approach to synthesizing decision trees that has been used in a variety of systems, and it describes one such system, ID3, in detail.
J. R. Quinlan
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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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Decision trees in epidemiological research
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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, 1990 This paper describes experiments, on two domains, to investigate the effect of averaging over predictions of multiple decision trees, instead of using a single tree. Other authors have pointed out theoretical and commonsense reasons for preferring the multiple tree approach.
Suk Wah Kwok, Chris Carter
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Bivariate decision trees [PDF]
, 1997 Decision tree methods constitute an important and much used technique for classification problems. When such trees are used in a Datamining and Knowledge Discovery context, ease of interpretation of the resulting trees is an important requirement to be met.
Jan C. Bioch +2 more
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