Results 21 to 30 of about 4,926,046 (277)
Learning Optimal Decision Trees Using Caching Branch-and-Bound Search
AAAI Conference on Artificial Intelligence, 2020 Several recent publications have studied the use of Mixed Integer Programming (MIP) for finding an optimal decision tree, that is, the best decision tree under formal requirements on accuracy, fairness or interpretability of the predictive model.
Gaël Aglin +2 more
semanticscholar +1 more source
DECISION TREES BASED ON MEMRISTOR TECHNOLOGY
Надежность и качество сложных систем, 2022 Background. Despite significant progress in neuroscience recently, understanding of the principles and mechanisms underlying complex brain functions and cognition remains incomplete.
A.Yu. Dorosinskiy +3 more
doaj +1 more source
Caspian Journal of Neurological Sciences, 2021 Background: Epilepsy is a brain disorder that changes the basin geometry of the oscillation of trajectories in the phase space. Nevertheless, recent studies on epilepsy often used the statistical characteristics of this space to diagnose epileptic ...
Reyhaneh Zarifiyan Irani Nezhad +4 more
doaj +1 more source
GBDT-MO: Gradient-Boosted Decision Trees for Multiple Outputs [PDF]
IEEE Transactions on Neural Networks and Learning Systems, 2019 Gradient-boosted decision trees (GBDTs) are widely used in machine learning, and the output of current GBDT implementations is a single variable. When there are multiple outputs, GBDT constructs multiple trees corresponding to the output variables.
Zhendong Zhang, Cheolkon Jung
semanticscholar +1 more source
Non-Invasive Meningitis Diagnosis Using Decision Trees
IEEE Access, 2020 Meningitis is one of the pandemic diseases that many less developed countries suffer, primarily due to the lack of economic resources to face it. The more severe types of meningitis, Meningococcal Disease, MD, demand immediate medical attention since ...
Viviane M. Lelis +2 more
doaj +1 more source
Private Boosted Decision Trees via Smooth Re-Weighting
The Journal of Privacy and Confidentiality, 2023 Protecting the privacy of people whose data is used by machine learning algorithms is important. Differential Privacy is the appropriate mathematical framework for formal guarantees of privacy, and boosted decision trees are a popular machine learning ...
Mohammadmahdi Jahanara +4 more
doaj +3 more sources
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
Secure training of decision trees with continuous attributes
IACR Cryptology ePrint Archive, 2020 We apply multiparty computation (MPC) techniques to show, given a database that is secret-shared among multiple mutually distrustful parties, how the parties may obliviously construct a decision tree based on the secret data.
Mark Abspoel +2 more
semanticscholar +1 more source
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
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