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dc.contributor.authorPatcharaporn Paokantaen_US
dc.contributor.authorSomdet Srichairatanakoolen_US
dc.date.accessioned2018-09-04T10:12:40Z-
dc.date.available2018-09-04T10:12:40Z-
dc.date.issued2015-01-01en_US
dc.identifier.issn13494198en_US
dc.identifier.other2-s2.0-84930248097en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84930248097&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/54383-
dc.description.abstract© 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.en_US
dc.subjectComputer Scienceen_US
dc.subjectMathematicsen_US
dc.titleA 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)en_US
dc.typeJournalen_US
article.title.sourcetitleInternational Journal of Innovative Computing, Information and Controlen_US
article.volume11en_US
article.stream.affiliationsChiang Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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