Sentence examples for estimating predictions from inspiring English sources

We focus on the three main issues introduced above: (1) use of imputation-specific or pooled regression coefficients for estimating predictions; (2) using predictions to estimate model performance measures and (3) the evaluation of the model performance in the context of future clinical settings where predictor information may be fully observed or partly missing.

Three main issues have been highlighted: (1) use of imputation-specific or pooled regression coefficients for estimating predictions; (2) the application of Rubin's rules to imputation-specific predictions or to model performance measures; and (3) the evaluation of the model performance in the context of future clinical settings where covariate information may be complete or partially missing.

This subsection presents an algorithm for estimating prediction error degrees using MKDA-based ordinal regression.

The above equation enables ordinal regression for estimating prediction error degrees.

A method for efficiently estimating prediction error bounds is presented and validated using representative parametric uncertainties.

Estimating prediction uncertainty for a single tree-based model is hindered by the complex structure of these models.

Various kinds of meteorological elements can be used for estimating prediction error degrees of a target meteorological element, and their features are heterogeneous.

Cross-validation is an alternative to the split sample method of estimating prediction accuracy (Radmacher et al, 2002).

The first, or outer, layer was for estimating prediction error and the second, or inner, layer for model selection (see Figure 2).

It is common to evaluate algorithms by estimating prediction accuracy via cross-validation for several datasets, with results summarized across datasets to rank algorithms (Boulesteix, 2013; Demšar, 2006).

A VAR model was estimated in order to compare the observed behavior with intervention measures and estimated predictions with a theoretically free market.