Results 71 to 80 of about 5,778,654 (336)
IEEE AccessThis paper investigates classes of decision tables (DTs) with 0-1-decisions that are closed under the removal of attributes (columns) and changes to the assigned decisions to rows.
Azimkhon Ostonov, Mikhail Moshkov
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Machine Learning Methods with Decision Forests for Parkinson’s Detection
Applied Sciences, 2021 Biomedical engineers prefer decision forests over traditional decision trees to design state-of-the-art Parkinson’s Detection Systems (PDS) on massive acoustic signal data.
Moumita Pramanik +4 more
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End-to-End Learning of Decision Trees and Forests
International Journal of Computer Vision, 2019 Conventional decision trees have a number of favorable properties, including a small computational footprint, interpretability, and the ability to learn from little training data.
Thomas M. Hehn +2 more
semanticscholar +1 more source
Screening for lung cancer: A systematic review of overdiagnosis and its implications
Molecular Oncology, EarlyView.Low‐dose computed tomography (CT) screening for lung cancer may increase overdiagnosis compared to no screening, though the risk is likely low versus chest X‐ray. Our review of 8 trials (84 660 participants) shows added costs. Further research with strict adherence to modern nodule management strategies may help determine the extent to which ...
Fiorella Karina Fernández‐Sáenz +12 more
wiley +1 more source
Method of decision tree applied in adopting the decision for promoting a company
Annals of Spiru Haret University Economic Series, 2015 The decision can be defined as the way chosen from several possible to achieve an objective. An important role in the functioning of the decisional-informational system is held by the decision-making methods.
Cezarina Adina TOFAN
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Decision trees, monotone functions, and semimatroids [PDF]
, 2013 We define decision trees for monotone functions on a simplicial complex. We define homology decidability of monotone functions, and show that various monotone functions related to semimatroids are homology decidable.
White, Jacob A.
core
MAPTree: Beating “Optimal” Decision Trees with Bayesian Decision Trees
Proceedings of the AAAI Conference on Artificial IntelligenceDecision trees remain one of the most popular machine learning models today, largely due to their out-of-the-box performance and interpretability. In this work, we present a Bayesian approach to decision tree induction via maximum a posteriori inference of a posterior distribution over trees.
Sullivan, Colin +2 more
openaire +2 more sources
Molecular Oncology, EarlyView.Development of therapies targeting cancer‐associated fibroblasts (CAFs) necessitates preclinical model systems that faithfully represent CAF–tumor biology. We established an in vitro coculture system of patient‐derived pancreatic CAFs and tumor cell lines and demonstrated its recapitulation of primary CAF–tumor biology with single‐cell transcriptomics ...
Elysia Saputra +10 more
wiley +1 more source
Team Decision Problems with Classical and Quantum Signals
, 2015 We study team decision problems where communication is not possible, but coordination among team members can be realized via signals in a shared environment.
Brandenburger, Adam +1 more
core +1 more source
A framework for sensitivity analysis of decision trees
Central European Journal of Operations Research, 2017 In the paper, we consider sequential decision problems with uncertainty, represented as decision trees. Sensitivity analysis is always a crucial element of decision making and in decision trees it often focuses on probabilities.
B. Kamiński +2 more
semanticscholar +1 more source