Results 11 to 20 of about 9,752,550 (347)
European Journal of Operational Research, 2021 In the context of credit scoring, ensemble methods based on decision trees, such as the random forest method, provide better classification performance than standard logistic regression models.
Elena Dumitrescu +3 more
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The clinical decision analysis using decision tree [PDF]
Epidemiology and Health, 2014 The clinical decision analysis (CDA) has used to overcome complexity and uncertainty in medical problems. The CDA is a tool allowing decision-makers to apply evidence-based medicine to make objective clinical decisions when faced with complex situations.
Jong-Myon Bae
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An Explainable Bayesian Decision Tree Algorithm
Frontiers in Applied Mathematics and Statistics, 2021 Bayesian Decision Trees provide a probabilistic framework that reduces the instability of Decision Trees while maintaining their explainability. While Markov Chain Monte Carlo methods are typically used to construct Bayesian Decision Trees, here we ...
Giuseppe Nuti +2 more
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Complex, 2021 Despite the growing popularity of machine learning models in the cyber-security applications (e.g., an intrusion detection system (IDS)), most of these models are perceived as a black-box.
Basim Mahbooba +3 more
semanticscholar +1 more source
Machine Learning, 1993 Quinlan and Rivest have suggested a decision-tree inference method using the Minimum Description Length idea. We show that there is an error in their derivation of message lengths, which fortunately has no effect on the final inference. We further suggest two improvements to their coding techniques, one removing an inefficiency in the description of ...
Chris S. Wallace, Jon D. Patrick
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Classification of Images Using Decision Tree [PDF]
Engineering and Technology Journal, 2013 In this paper, the proposed system is based on texture features classification for multi object images by using decision tree (ID3) algorithm. The proposed system uses image segment tile base to reduce the block effect and uses (low low) Wavelet Haar to ...
Emad K. Jabbar, Mayada jabbar kelain
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A Two-Parameter Fractional Tsallis Decision Tree
Entropy, 2022 Decision trees are decision support data mining tools that create, as the name suggests, a tree-like model. The classical C4.5 decision tree, based on the Shannon entropy, is a simple algorithm to calculate the gain ratio and then split the attributes ...
Jazmín S. De la Cruz-García +2 more
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Improved version of explainable decision forest: Forest-Based Tree [PDF]
IJCI International Journal of Computers and Information, 2023 A Decision Forest is an ensemble learning method that seeks to enhance the predictivity of a single decision tree via training several trees and combining their decisions.
Faten Khalifa +2 more
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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 Irsoy, Ethem Alpaydin
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