Results 31 to 40 of about 169,825 (305)
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
doaj +1 more source
, 2021 This is the first release of Interactive Decision Trees package. It contains Python modules that enable the user to interact with the Decision Tree by creating new composite variables, grouping the input variables and color code the groups, selecting ...
Pianosi, Francesca +2 more
core +1 more source
Boosted Decision Trees and Applications
EPJ Web of Conferences, 2013 Decision trees are a machine learning technique more and more commonly used in high energy physics, while it has been widely used in the social sciences.
Coadou Yann
doaj +1 more source
IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 2012 Licensed copy is available on IEEE ...
Manwani, N, Sastry, PS
openaire +3 more sources
Design of Neuro-Fuzzy Decision Trees
MATEC Web of Conferences, 2016 In order to improve accuracy of fuzzy decision trees classification we propose a procedure of parameters adaptation by means of neural network training.
Abramova Tatyana
doaj +1 more source
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
core +1 more source
Data-Driven EEG Band Discovery with Decision Trees
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 +1 more source
Quantum Speedup Based on Classical Decision Trees [PDF]
Quantum, 2020 Lin and Lin \cite{LL16} have recently shown how starting with a classical query algorithm (decision tree) for a function, we may find upper bounds on its quantum query complexity. More precisely, they have shown that given a decision tree for a function $
Salman Beigi, Leila Taghavi
doaj +1 more source
Multi-test Decision Tree and its Application to Microarray Data Classification [PDF]
, 2014 Objective: The desirable property of tools used to investigate biological data is easy to understand models and predictive decisions. Decision trees are particularly promising in this regard due to their comprehensible nature that resembles the ...
Marcin Czajkowski +5 more
core +1 more source
International Journal of Prognostics and Health Management, 2013 This study presents the methods employed by a team from the department of Mechatronics and Dynamics at the University of Paderborn, Germany for the 2013 PHM data challenge.
James K. Kimotho +3 more
doaj +1 more source