A new algorithm of ensemble learning for medical knowledge-based systems and knowledge-based systems: Hybrid Bayesian computing (multinomial logistic regression case-based C5.0-mixed classification and regression tree)

© 2015 ICIC International. This paper attempts to answer the question “How to construct and apply the novel algorithm based on Ensemble Learning approach called Bayesian Mixed Probability Distributions-CBR-C5.0-CART for Medical Knowledge-Based Systems and Knowledge-Based Systems (KBSs)?” The finding...

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Main Authors: Patcharaporn Paokanta, Somdet Srichairatanakool
格式: 雜誌
出版: 2018
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在線閱讀:https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84930248097&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/44449
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機構: Chiang Mai University
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總結:© 2015 ICIC International. This paper attempts to answer the question “How to construct and apply the novel algorithm based on Ensemble Learning approach called Bayesian Mixed Probability Distributions-CBR-C5.0-CART for Medical Knowledge-Based Systems and Knowledge-Based Systems (KBSs)?” The finding of this study is the new algorithm of Bayesian-Mixed Probability Distributions-C5.0-CART which is developed for the inference engines of KBSs. The proposed algorithm is applied to Thalassemia data set including F-cell, HbA < inf > 2 < /inf > , and Inclusion Body of Thalassemia patients. These are collected from medical practitioner and scientist who are the experts in Thalassemia diagnosis. In the future, this algorithm and a new collected data set will be combined with graph theory to generate the new theory called Ramsey Graph Bayesian-Mixed Probability Distributions for Digital Images Processing and Images Processing.