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Ensemble Classification Method for Efficient Medical Diagnostic  

Jung, Yong-Gyu (을지대학교 의료IT마케팅학과)
Heo, Go-Eun (을지대학교 의료산업학부 의료전산학전공)
Publication Information
The Journal of the Institute of Internet, Broadcasting and Communication / v.10, no.3, 2010 , pp. 97-102 More about this Journal
Abstract
The purpose of medical data mining for efficient algorithms and techniques throughout the various diseases is to increase the reliability of estimates to classify. Previous studies, an algorithm based on a single model, and even the existence of the model to better predict the classification accuracy of multi-model ensemble-based research techniques are being applied. In this paper, the higher the medical data to predict the reliability of the existing scope of the ensemble technique applied to the I-ENSEMBLE offers. Data for the diagnosis of hypothyroidism is the result of applying the experimental technique, a representative ensemble Bagging, Boosting, Stacking technique significantly improved accuracy compared to all existing, respectively. In addition, compared to traditional single-model techniques and ensemble techniques Multi modeling when applied to represent the effects were more pronounced.
Keywords
Ensemble-based; Bagging; Boosting; Stacking; I-ENSEMBLE;
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Times Cited By KSCI : 1  (Citation Analysis)
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