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Gheyyem et al. introduced an empirical correlation based on regression method.
Most of the models based on regression method (RM) have some restrictive assumptions.
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Although improved precisions continue to be reported at times, almost all are based on regression methods empirically, while the accuracy is often not properly addressed.
Other methods, such as neural network approach or methods based on regression modeling, have also been used in the past [14, 15, 16].
We present an adaptive method based on regression analysis that enables dynamic switching at runtime with little overhead.
We tried to solve the problem of the authority estimation within the web discussion forum using a machine learning method based on regression analysis.
We applied a 2-step standardization method based on regression residuals.
R.S. suggested the 2-step standardization method based on regression residuals.
To limit the impact of between-subject variations in urine sampling conditions, we standardized biomarker concentrations using a two-step standardization method based on regression residuals.
Here, we generalize this approach to the situation where several sampling conditions are considered simultaneously, using a 2-step standardization method based on regression residuals.
We used a two-step standardization method based on regression residuals to reduce undesirable variability in biomarker urinary concentrations due to sampling conditions.
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