• 디지털콘텐츠학회 논문지
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• 제19권4호
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• pp.739-747
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• 2018

고차원 데이터에서는 데이터마이닝 기법 중에서 특징 선택은 매우 중요한 과정이 되었다. 그러나 전통적인 단일 특징 선택방법은 더 이상 효율적인 특징선택 기법으로 적합하지 않을 수 있다. 본 논문에서 우리는 고차원 데이터에 대한 효율적인 특징선택을 위하여 혼합형 특징선택 기법을 제안하였다. 본 논문에서는 KNHANES 데이터에 제안한 혼합형 특징선택기법을 적용하여 분류한 결과 기존의 분류기법을 적용한 모델보다 5% 이상의 정확도가 향상되었다.

• 대한지역사회영양학회지
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• 제25권2호
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• pp.150-158
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• 2020

Objectives: This study was conducted to estimate usual meat intake distribution, which may have been over/underestimated when estimations were made using only the third food codes of the Korea National Health and Nutrition Examination Survey (KNHANES). Methods: For this purpose, 24-hour recall data from the 2009 Korea National Health and Nutrition Examination Survey, which conducted a partial 2-day survey of food intake, were used. The Multiple Source Method (MSM) was used to estimate the distribution of the usual intake of red and processed meats. Results: The results of this study show that the mean intake of red meat was 45.07 g while that of processed meat was 4.33 g. These results are slightly higher than the consumption calculated using only tertiary food code, and the difference was statistically significant. Furthermore, characteristics of the estimated usual intake distribution were a smaller standard deviation, increased lower percentiles, and decreased upper percentiles compared to the 2-day mean intake distribution for both red and processed meats. The proportion of individuals not consuming red meat decreased substantially from approximately 37% to 0.7%. The proportion of consumption that exceeded 90 g, which is the upper limit of red meat intake recommended by the National Health Service (NHS), was only approximately 10% in the distribution of usual intake. Conclusions: As the consumption of processed foods is expected to continuously increase, caution is needed regarding the processes used to calculate food (group) intake to avoid over/underestimation. Moreover, use of KNHANES data to calculate the proportion of the population at risk of insufficiency or excess intake of certain nutrients or food (group), based on one day intake that does not address within-individual variation, may lead to biased estimates.