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
doaj +7 more sources
Tree in Tree: from Decision Trees to Decision Graphs [PDF]
arXiv, 2021 Decision trees have been widely used as classifiers in many machine learning applications thanks to their lightweight and interpretable decision process. This paper introduces Tree in Tree decision graph (TnT), a framework that extends the conventional decision tree to a more generic and powerful directed acyclic graph.
Zhu, Bingzhao, Shoaran, Mahsa
arxiv +3 more sources
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
doaj +2 more sources
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
doaj +2 more sources
Quantum computation and decision trees [PDF]
, 1998 Many interesting computational problems can be reformulated in terms of decision trees. A natural classical algorithm is to then run a random walk on the tree, starting at the root, to see if the tree contains a node n levels from the root.
Edward Farhi, Sam Gutmann
openalex +3 more sources
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
doaj +2 more sources
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
doaj +2 more sources
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
doaj +2 more sources
Decision Rules Derived from Optimal Decision Trees with Hypotheses [PDF]
Entropy, 2021 Conventional decision trees use queries each of which is based on one attribute. In this study, we also examine decision trees that handle additional queries based on hypotheses.
Mohammad Azad +4 more
doaj +2 more sources
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
doaj +2 more sources