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The best predictive model contained a model of nitrate leaching but no land use information, implying that changes in land use will not affect designations based upon this model.
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Using this methodology, a final predictive model containing just the important variables will be created.
The first stepwise linear regression included in Table 5 contains the best predictive model selected for the VG total score, considering the sociodemographic variables and the personality profile measured via the TCI-R questionnaire as independent variables.
The 2006 turbidity prediction model was selected as the best predictive model because of its ability to predict turbidity within the acceptable error range and required confidence interval.
Finally, based on the best feature combination, we developed one best predictive model set and applied it to predict the primary tumor sites.
Further studies in different patient groups with different models are needed to determine the best predictive model.
Then, stepwise linear regression analysis was performed to identify the best predictive model using important parameters.
The quadratic model was found to be the best predictive model for describing the cooking behavior of rice.
The total number of peaks yielded the best predictive model and is used for optimization of parameters setting.
We performed cross-validation to test the predictive ability of the different models and to find the best predictive model.
The best predictive model accounted for 34% of the variance (R = 0.34, see Table 4).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com