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In addition, the statistical analysis indicates that MLR model with reasonable variable selection (SPA-MLR) could exhibit a slight superiority toward PLS-1 in the system.
Of variables that were highly correlated (phi coefficient > 0.4), the more reasonable variable was selected for the multivariable analysis.
Considering that a high training accuracy does not entail a high prediction accuracy, we developed a new feature selection algorithm called gradient method to find reasonable variable features across multiple classes.
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As SVO and LVA were ad hoc determined scientifically reasonable variables correction for multiple testing was not primarily applied.
RMT/DIF analyses thus provide a complementary method alongside standard testing for examining key clinically reasonable variables, with the intention of flagging issues with DIF for further examination.
From the variables that proved significant in bivariate analyses, reasonable variables were chosen for multiple linear regression with EQ VAS, EQ-5D index score, and FAMS sum score as dependent variables.
In order to confirm that the imputed values are reasonable, each variable with missing data in excess of 8% was examined to identify variables with large differences between the measured and imputed.
An acceptable level of misfit (i.e., matching gravity data uncertainty) can be achieved using the existing 3D geologic model and allowing geologically reasonable, but variable density values in the individual rock units.
At both KMH and TSU, there is reasonable, but variable, agreement between the data and both models, and from the visual comparison, a general statement which of the models fits the data better is not possible.
Next we needed to select reasonable predictor variables and compile a set of data.
Finally, reasonable design variables are selected by applying fuzzy logic inference.
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