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Equation 3 is specific to binary or categorical classification; a similar expression can be derived for regression.
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Similar regression models can be derived for Scenarios 2 and 3 as well.
Similar expressions can be derived for the case of predicting real-valued outputs using linear regression.
Because four dietary patterns were derived for this sample, four linear regression models were fitted to explore the associations.
Separate regression coefficients were derived for each age group and end point [half-life, clearance, AUC, volume of distribution (Vd)], with the regression coefficient representing the age group:young adult ratio of parameter values.
In particular, non-constant peak factor expressions via regression analysis are derived for various ground-motion durations.
Few quadratic regression equations were derived for different regions of Bangladesh.
For the increase rate of the capillary pores following the mixing of the expansive additive, a regression equation was derived for the admixture of the expansive additive and the increase rate of the pores, as shown in Fig. 11.
Separate multivariable (logistic) regression models were derived for FABP7 early (day 1) and late (days 3 5) by including variables, which were significant on univariate analysis and performing backward elimination with a p value threshold of 0.05.
In addition, a regression equation was derived for predicting the presence of esophageal varices.
Individual logistic regression models were derived for each of the three cancer definitions from the training cohort.
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