Results 11 to 20 of about 741,105 (343)
TNT: An Interpretable Tree-Network-Tree Learning Framework using Knowledge Distillation
Entropy, 2020 Deep Neural Networks (DNNs) usually work in an end-to-end manner. This makes the trained DNNs easy to use, but they remain an ambiguous decision process for every test case.
Jiawei Li +5 more
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Computers and Education: Artificial Intelligence, 2021 In the area of machine learning and data science, decision tree learning is considered as one of the most popular classification techniques. Therefore, a decision tree algorithm generates a classification and predictive model, which is simple to ...
Vasiliki Matzavela, Efthimios Alepis
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Learning Decision Trees Recurrently Through Communication
2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021 Integrated interpretability without sacrificing the prediction accuracy of decision making algorithms has the potential of greatly improving their value to the user. Instead of assigning a label to an image directly, we propose to learn iterative binary sub-decisions, inducing sparsity and transparency in the decision making process.
Alaniz, Stephan +3 more
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Agnostically learning decision trees [PDF]
Proceedings of the fortieth annual ACM symposium on Theory of computing, 2008 We give a query algorithm for agnostically learning decision trees with respect to the uniform distribution on inputs. Given black-box access to an *arbitrary* binary function f on the n-dimensional hypercube, our algorithm finds a function that agrees with f on almost (within an epsilon fraction) as many inputs as the best size-t decision tree, in ...
Parikshit Gopalan +2 more
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Evolutionary Learning of Interpretable Decision Trees
IEEE Access, 2023 69 pages, 31 figures, code available at: https://gitlab.com/leocus ...
Custode, Leonardo Lucio, Iacca, Giovanni
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Application of Decision Tree-Based Classification Algorithm on Content Marketing
Journal of Mathematics, 2022 Traditional content marketing methods resort grossly to market requirements but barely obtain relatively accurate marketing prediction under loads of requirements.
Yi Liu, Shuo Yang
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On Laws of Thought—A Quantum-like Machine Learning Approach
Entropy, 2023 Incorporating insights from quantum theory, we propose a machine learning-based decision-making model, including a logic tree and a value tree; a genetic programming algorithm is applied to optimize both the logic tree and value tree.
Lizhi Xin, Kevin Xin, Houwen Xin
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Attribute Selection Based on Constraint Gain and Depth Optimal for a Decision Tree
Entropy, 2019 Uncertainty evaluation based on statistical probabilistic information entropy is a commonly used mechanism for a heuristic method construction of decision tree learning.
Huaining Sun, Xuegang Hu, Yuhong Zhang
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The Evaluation of Online Education Course Performance Using Decision Tree Mining Algorithm
Complexity, 2021 With the continuous development of “Internet + Education”, online learning has become a hot topic of concern. Decision tree is an important technique for solving classification problems from a set of random and unordered data sets.
Yongxian Yang
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Educational Data Mining Using Cluster Analysis Methods and Decision Trees based on Log Mining
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi), 2022 Educational Data Mining (EDM) often appears to be applied in big data processing in the education sector. One of the educational data that can be further processed with EDM is activity log data from an e-learning system used in teaching and learning ...
Safira Nuri Safitri +2 more
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