Sentence examples for multiple predictors to from inspiring English sources

The second category of models we are interested in analyzing is that of VQA using multiple predictors to accomplish quality estimation.

Clinical prediction rules are evidence-based tools that combine multiple predictors to estimate the probability that a particular outcome in an individual patient will occur.

For each of the 11 influenza seasons, we applied negative binomial regression models with multiple predictors to relate the weekly IPP rates with the indicators of influenza and RSV activities while adjusting for the weekly mean temperature, total sunshine, and total precipitation.

Multiple predictors, related to physical environment (e.g. climate), land use (e.g. crop area), and landscape structure (e.g. mean patch size), were found to influence diversity patterns, even under the homogenizing effects of agricultural intensification.

Because of its simplicity and ability to represent multiple predictor variables to improve the fitted model, this paper proposes use of the logit formulation of the fragility function at the system level for two or more simultaneous weather hazards.

Finally, for exposure biomarkers with multiple significant predictors, to explore confounding we constructed multivariable models where these predictors were included simultaneously.

In a typical application, a classification model is used to combine multiple biomarkers (predictors) to predict a binary outcome such as diseased/nondiseased, responders/non-responders to therapy, etc.

We used the Cox proportional hazard model to evaluate multiple predictors of outcome and to eliminate confounding factors.

(1) (2) Linear regression models are useful for quantifying the relationships between multiple predictor variables to a response variable.

Local traders are constructed with pattern-based multiple predictors, and used to decide the purchase money per recommendation.

Although multiple predictors were obtained to cover as many aspects and processes that could affect the distribution of benthic standing stocks, around 19% to 36% of observed variances are still unexplainable in the current RF models.