Sentence examples for multiple predictors for from inspiring English sources

The rationale behind using multiple predictors for quality assessment is that different types of signals might map into quality differently, and thus, using specialized predictors for each signal type would bring to more accurate quality estimations.

Therefore, the cost-sensitive ensemble algorithm that incorporates cost-sensitive scheme produces more robust performance than conventional ensemble simply combining multiple predictors for predicting.

When simultaneously evaluating multiple predictors for disease outcome, current methods focus on building multivariable models, rather than the evaluation of single exposures adjusting for known covariates [ 15].

We developed logistic regression models to assess for the multiple predictors of poor quality drug (generic drug class, type of outlet, country of origin, tablet packaging and appearance and size of trading centre), as well as potential interaction terms.

The results of odds ratios of multiple predictors were used for the purpose of detection of the specific causes of factors that affect child mortality in Tanzania.

Where e = probability (Y = outcome of interest| X = x) =Extending the logit model for multiple predictors, a complex logistic model can be constricted as follows- = α + β 1 x 1 + β 2 x 2 + ��� … + β k x k (4).

After controlling for multiple predictors, vasopressor use remained associated with time to death (HR 9.9; 95% CI 2.3 43.3; P = 0.002).

Extending (2a) to account for multiple predictors, the conditional expectation function can be written as (6) g j (x i j k ) = E [ (y i − ∑ j ′ = 1 j ′ ≠ j N ∑ k = 1 2 g j ′ (x i j ′ k ) | x i j k ) ]. Assuming additivity of the predictors, this leads to the following iterative backfitting algorithm [ 12, 5] for computing the functions.

The threshold applies to the entire linear combination of multiple predictors, which implies that for the same amount of early weight gain, patients may be predicted to gain substantial weight or not gain substantial weight depending on the values for other characteristics included in the prediction model.

Similarly, the correlation was stronger between MinT and LAI and between MinT and FCover compared to elevation, and we excluded elevation from multiple predictor models for both canopy structure variables.

2010), because precipitation is associated with larger model uncertainty, and downscaling relationships are generally more complex (i.e., including multiple predictors and non-linear relationships) than for air temperature predictands.