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The prediction is through checking the change in the probability ratio for classification after a feature is excluded from predictors of a classifier that employs the selected features (see Methods).
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15 We calculated sensitivity, specificity, and likelihood ratios for classification as high urgency and low urgency (likelihood ratio+=sensitivity/(1−specificity) and likelihood ratio−=(1−sensitivity)/specificity).
To identify the most important predictors of mutation status to be used in estimation of the likelihood ratios for classification of variants, we undertook a series of logistic regression analyses.
However, the compatibility ratio for the classification of MV deaths between ICD-9 and ICD-10 is 0.9545 indicating that this classification change might have a minimal impact on MV fatality trends (Anderson et al. 2001).
Specifically, the correct classification ratio for SW, SG and DG were 95.7, 54.2 and 63.6 %, respectively by applying the discriminant functions (Table 4).
For classification problems, the Fisher Discriminant Ratio [64] is often used because it is simple to compute and reliable for binary classification problems.
Since the tested datasets have an imbalanced ratio between number of samples in positive and negative class, accuracy is not a good measure for classification performance.
These models were adjusted for age, ln-urinary creatinine, sex, race/ethnicity, family poverty income ratio, BMI classification, and survey cycle.
Normalized ΔCt data were used for classification.
This concatenated feature was used for classification.
‡p<0.01 for classification index.
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