Results 31 to 40 of about 5,778,654 (336)
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
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
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
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
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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
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
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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
Learning Optimal and Fair Decision Trees for Non-Discriminative Decision-Making [PDF]
AAAI Conference on Artificial Intelligence, 2019 In recent years, automated data-driven decision-making systems have enjoyed a tremendous success in a variety of fields (e.g., to make product recommendations, or to guide the production of entertainment). More recently, these algorithms are increasingly
S. Aghaei, Javad Azizi, Phebe Vayanos
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
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