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Music rhythm tree based partitioning approach to decision tree classifier
Journal of King Saud University: Computer and Information Sciences, 2022 Decision tree is a widely used non-parametric technique in machine learning, data mining and pattern recognition. It is simple to understand and interpret, however it faces challenges such as handling higher dimensional and class imbalanced datasets ...
Shankru Guggari +3 more
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Implementation of the Decission Tree Algorithm to Determine Credit Worthiness
Compiler, 2023 Credit is a loan from a bank that needs to be repaid with interest. In practice, problematic credit or bad credit often occurs due to less thorough credit analysis in the credit granting process, or from bad customers.
Abdussomad Abdussomad +2 more
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Decision Tree Algorithm-based API Misuse Detection [PDF]
Jisuanji kexue, 2022 Application programming interface(API) benefits to effectively improve software development efficiency by reusing existing software frameworks or libraries.However,many constraints must be satisfied to correctly use APIs,such as call order,exception ...
LI Kang-le, REN Zhi-lei, ZHOU Zhi-de, JIANG He
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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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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, E, Alpaydin
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Multivariate decision trees [PDF]
Machine Learning, 1995 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Brodley, Carla E., Utgoff, Paul E.
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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 ...
Wallace, C. S., Patrick, J. D.
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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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