Sentence examples for combination of predictors from inspiring English sources

The linear regression analysis shows that although increased expression of HER2 is the best single predictor for responsiveness to AG1478 or the AG1478-trastuzumab combinasion (as well as for trastuzumab alone), the best combination of predictors for the efficacy of AG1478 or combined AG1478-trastuzumab increasedsexpressioniof of the EGFR and HER3 (Table 2).

Model selection maximized the cross-validated log-likelihood ratio by finding the best combination of predictors and the smoothing parameter (tolerance) for each predictor.

This is the first study to conduct sex-specific longitudinal analyses in a paediatric headache sample of children and adolescents (9 to 14 years old at first wave) using this kind of method and a combination of predictors.

This selective combination of predictors aims to project data onto a lower dimension space while retaining as much information as possible by eliminating the correlated information caused by overlapping input.

In this study we used Mallow's C p statistics [67], a combination of predictors that minimizes the Mallow C p over all possible subsets, was considered as the best subset for model development.

The neural network models achieved accuracies ranging from 3%to10%0% depending on the combination of predictors such as ambient temperature, pressure, relative humidity, cloudiness, wind speed and wind direction.

Then a multiple regression analysis conducted for each combination of Predictor 1 and Predictor 2 provided us with the best predictor for each behavioral parameter with its contribution (defined by the R-squared).

The combination of predictor variables has only a slight effect on the APA, but a profound effect on the PAP.

The purpose of this study was to identify a single combination of predictor tests that would predict physical performance on all of the criterion measure task simulations relevant to the Combat Arms military occupational specialties.

The challenge is to determine an optimal combination of predictor variables that best describes the phenomenon of interest, without resulting in overparameterization of the model.

The combination of predictor variables required for each risk score varied with the score being validated as shown in table 1.