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Please use this identifier to cite or link to this item: http://ir.ncue.edu.tw/ir/handle/987654321/12693

Title: Prediction of Allergy Symptoms among Children in Taiwan Using Data Mining
Authors: Ng, Hui-Fuang;Fathoni Halim;Chen, I-Chi
Contributors: 人力資源管理所
Keywords: Allergy Symptoms;Data Mining;Children
Date: 2009-10
Issue Date: 2012-07-27T02:33:45Z
Abstract: Allergic diseases have increased in children in many countries with modern living conditions. This study used data mining techniques to construct predictive models for prediction of allergy symptom among children in Taiwan from survey data. Among three predictive models, the decision tree model gives the best overall result, with a classification accuracy of 70.3%, followed by neural networks (69.6%) and support vector machine (66.4%). Results indicate that children exposed to environment that contains allergy inducing agents are key factors that trigger allergy symptoms. Family factors, especially heredity factors, are also important factors of children allergy.
Relation: Joint Conference on Medical Informatics in Taiwan, Taipei, Taiwan, 2009年10月3-4日
Appears in Collections:[人力資源管理研究所] 會議論文

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