Results 31 to 40 of about 4,926,046 (277)
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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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
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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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Encyclopedia of Database Systems, 2018 Linear regressors from X = R to Y = R have a limited expressive power, because they fit K affine functions to the training set. Functions that are more complex than that are approximated poorly.
Alin Dobra
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Efficient Inference of Optimal Decision Trees
AAAI Conference on Artificial Intelligence, 2020 Inferring a decision tree from a given dataset is a classic problem in machine learning. This problem consists of building, from a labelled dataset, a tree where each node corresponds to a class and a path between the tree root and a leaf corresponds to ...
Florent Avellaneda
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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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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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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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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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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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