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This paper describes experiments, on two domains, to investigate the effect of averaging over predictions of multiple decision trees, instead of using a single tree. Other authors have pointed out theoretical and commonsense reasons for preferring the multiple tree approach.
Suk Wah Kwok, Chris Carter
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Bivariate decision trees [PDF]
Decision tree methods constitute an important and much used technique for classification problems. When such trees are used in a Datamining and Knowledge Discovery context, ease of interpretation of the resulting trees is an important requirement to be met.
Jan C. Bioch+2 more
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Decision trees in epidemiological research [PDF]
Abstract Background In many studies, it is of interest to identify population subgroups that are relatively homogeneous with respect to an outcome. The nature of these subgroups can provide insight into effect mechanisms and suggest targets for tailored interventions.
Nathan R. Mitchell+5 more
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Comparison of the use of binary decision trees and neural networks in top-quark detection [PDF]
The use of neural networks for signal vs.~background discrimination in high-energy physics experiment has been investigated and has compared favorably with the efficiency of traditional kinematic cuts.
David Bowser-Chao, Debra Lynn Dzialo
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Decision Tree Algorithm-based API Misuse Detection [PDF]
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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Implementation of the Decission Tree Algorithm to Determine Credit Worthiness
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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The clinical decision analysis using decision tree [PDF]
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
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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