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자료유형
학술저널
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한국자료분석학회 Journal of The Korean Data Analysis Society Journal of The Korean Data Analysis Society 제18권 제4호
발행연도
2016.1
수록면
1,741 - 1,750 (10page)

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Balance among the numbers of samples classified by their respective phenotypic classes would affect the results of the genomic association assessments. However it may not be always possible to maintain the balance or there may not be even clear balancing condition, especially with multi-class datasets. It would be desirable to have a method that is able to persistently give a consistent and correct estimation against a certain amount of change or imbalance between the phenotypic classes. We propose to examine the variance of an association measure on an ensemble of confusion matrices formed by assigning the possible combinations of the predicted class to each multifactor genotype without an effort to specify the single best set. Detection power of our method was retained through intentional un-balancing when odd ratio-based estimation showed continuous drop in the detection power. It was found that only 10% of the complete set of predicted class would yield sufficient result. Improvement was obvious and therefore the proposed method may not require the strict balance among the phenotypic classes to assess the correct genomic association.

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