Results 41 to 50 of about 4,859,475 (319)
IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 2012 Licensed copy is available on IEEE ...
Manwani, N, Sastry, PS
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Learning Explainable Decision Rules via Maximum Satisfiability
IEEE Access, 2020 Decision trees are a popular choice for providing explainable machine learning, since they make explicit how different features contribute towards the prediction.
Henrik E. C. Cao +2 more
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Interpreting CNNs via Decision Trees [PDF]
Computer Vision and Pattern Recognition, 2018 This paper aims to quantitatively explain the rationales of each prediction that is made by a pre-trained convolutional neural network (CNN). We propose to learn a decision tree, which clarifies the specific reason for each prediction made by the CNN at ...
Quanshi Zhang +3 more
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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
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Privacy-Preserving Gradient Boosting Decision Trees [PDF]
AAAI Conference on Artificial Intelligence, 2019 The Gradient Boosting Decision Tree (GBDT) is a popular machine learning model for various tasks in recent years. In this paper, we study how to improve model accuracy of GBDT while preserving the strong guarantee of differential privacy. Sensitivity and
Q. Li +3 more
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KnowledgeKnowledge comes in various forms: scientific, artistic, legal, and many others. For most non-computer scientists, it is far easier to express their knowledge in text than in programming code.
Joseph Vidal +5 more
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IEEE Access, 2022 We propose a new ML model called Topological Forest that contains an ensemble of decision trees. Unlike a vanilla Random Forest, Topological Forest has a special training process that selects a smaller number of decision trees on a topological graph ...
Murat Ali Bayir +3 more
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Omnivariate decision trees [PDF]
IEEE Transactions on Neural Networks, 2001 Univariate decision trees at each decision node consider the value of only one feature leading to axis-aligned splits. In a linear multivariate decision tree, each decision node divides the input space into two with a hyperplane. In a nonlinear multivariate tree, a multilayer perceptron at each node divides the input space arbitrarily, at the expense ...
C.T. Yildiz, Ethem Alpaydin
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A Survey of Decision Trees: Concepts, Algorithms, and Applications
IEEE AccessMachine learning (ML) has been instrumental in solving complex problems and significantly advancing different areas of our lives. Decision tree-based methods have gained significant popularity among the diverse range of ML algorithms due to their ...
Ibomoiye Domor Mienye, N. Jere
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