Results 11 to 20 of about 305,651 (314)
Tree in Tree: from Decision Trees to Decision Graphs
CoRR, 2021 Decision trees have been widely used as classifiers in many machine learning applications thanks to their lightweight and interpretable decision process. This paper introduces Tree in Tree decision graph (TnT), a framework that extends the conventional decision tree to a more generic and powerful directed acyclic graph.
Bingzhao Zhu, Mahsa Shoaran
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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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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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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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Multivariate decision trees [PDF]
Machine Learning, 1995 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Carla E. Brodley, Paul E. Utgoff
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Orthogonal decision trees [PDF]
IEEE Transactions on Knowledge and Data Engineering, 2006 This paper introduces orthogonal decision trees that offer an effective way to construct a redundancy-free, accurate, and meaningful representation of large decision-tree-ensembles often created by popular techniques such as bagging, boosting, random forests, and many distributed and data stream mining algorithms.
Hillol Kargupta +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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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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