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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/40197

Title: Receiver operating characteristic for diagnosis of wine quality by Bayesian network classifiers
Authors: Chih Chiang Wei
Contributors: 國立臺灣海洋大學:海洋環境資訊學系
Keywords: Receiver Operating Characteristic
Bayesian Network (BN)
Date: 2012-11
Issue Date: 2017-01-16T03:50:54Z
Publisher: Advanced Materials Research
Abstract: Abstract: This paper is dedicated to demonstrate the use of the receiver operating characteristic (ROC) and the area under the ROC curve (AUC) for diagnosing forecast skill. Several local search heuristic algorithms to discover which one performs better for learning a certain Bayesian networks (BN). Five heuristic search algorithms, including K2, Hill Climbing, Repeated Hill Climber, LAGD Hill Climbing, and TAN, were empirically evaluated and compared. This study tests BN models in a real-world case, the Vinho Verde wine taste preferences. An average AUC of 0.746 and 0.727 respectively in red wine and white wine were obtained by TAN algorithm. The results show that the use of TAN can effectively improve the AUC measures for predicting quality grade.
Relation: 591-593
URI: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/40197
Appears in Collections:[海洋環境資訊系] 期刊論文

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