Results 11 to 20 of about 785,617 (209)
Decision trees for regular factorial languages
Array, 2022 In this paper, we study arbitrary regular factorial languages over a finite alphabet Σ. For the set of words L(n)of the length n belonging to a regular factorial language L, we investigate the depth of decision trees solving the recognition and the ...
Mikhail Moshkov
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Optimization of decision trees using modified African buffalo algorithm
Journal of King Saud University: Computer and Information Sciences, 2022 Decision tree induction is a simple, however powerful learning and classification tool to discover knowledge from the database. The volume of data in databases is growing to quite large sizes, both in the number of attributes and instances.
Archana R. Panhalkar, Dharmpal D. Doye
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, 2022 Recently proposed budding tree is a decision tree algorithm in which every node is part internal node and part leaf. This allows representing every decision tree in a continuous parameter space, and therefore a budding tree can be jointly trained with backpropagation, like a neural network.
Ozan İrsoy, Ethem Alpaydın
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A Bi-criteria optimization model for adjusting the decision tree parameters
Kuwait Journal of Science, 2022 Decision trees play a very important role in knowledge representation because of its simplicity and self-explanatory nature. We study the optimization of the parameters of the decision trees to find a shorter as well as more accurate decision tree ...
Mohammad Azad, Mikhail Moshkov
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Tree in Tree: from Decision Trees to Decision Graphs
, 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
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FFTrees: A toolbox to create, visualize, and evaluate fast-and-frugal decision trees [PDF]
Judgment and Decision Making, 2017 Fast-and-frugal trees (FFTs) are simple algorithms that facilitate efficient and accurate decisions based on limited information. But despite their successful use in many applied domains, there is no widely available toolbox that allows anyone to easily ...
Nathaniel D. Phillips +3 more
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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
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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
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Improved Random Forest Algorithm Based on Out-of-Bag Prediction and Extended Space [PDF]
Jisuanji gongcheng, 2022 On the basis of the bootstrap method, the random forest algorithm constructs a decision tree by using sampling characteristics.This reduces the correlation among decision trees at the expense of decision tree accuracy, thereby improving the prediction ...
CHANG Shuo, ZHANG Yanchun
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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
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