Results 11 to 20 of about 6,176,379 (373)
Evidential Decision Tree Based on Belief Entropy
Entropy, 2019 Decision Tree is widely applied in many areas, such as classification and recognition. Traditional information entropy and Pearson’s correlation coefficient are often applied as measures of splitting rules to find the best splitting attribute ...
Mujin Li, Honghui Xu, Yong Deng
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Classification Based on Decision Tree Algorithm for Machine Learning
Journal of Applied Science and Technology Trends, 2021 Decision tree classifiers are regarded to be a standout of the most well-known methods to data classification representation of classifiers. Different researchers from various fields and backgrounds have considered the problem of extending a decision ...
Bahzad Charbuty, A. Abdulazeez
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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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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
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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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SAT-based Decision Tree Learning for Large Data Sets
AAAI Conference on Artificial Intelligence, 2021 Decision trees of low depth are beneficial for understanding and interpreting the data they represent. Unfortunately, finding a decision tree of lowest depth that correctly represents given data is NP-hard.
André Schidler, Stefan Szeider
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