Sentence examples for predictions using regression from inspiring English sources

We decided to try using Amazon Machine Learning (AML) to train a model and perform predictions using regression analysis.

We tested the predictions using regression models that incorporated phylogenetic information scaled by the degree of phylogenetic signal in the residuals (see below).

Surrogate stature measurement methods using sliding calipers, self-reporting of height and predictions using regression equations have been reported.

We therefore calculated CA and IA predictions using regression models for all single components that did not include a threshold parameter.

This approach is analogous to generating predictions using regression, then kriging the residuals and adding the results together except that all modeling stages are conducted simultaneously using generalized least squares to ensure correct estimation of the prediction errors [ 28].

To evaluate whether it would be possible to get a reasonable estimate for the Niederer-model parameters by direct prediction using regression, an inverse metamodel, predicting the input parameter values from the simulated output metrics in Table  2 and Table  3, was generated using Hierarchical Cluster-based Partial Least Squares Regression (HC-PLSR) [ 5, 6].

We put forward GRASP as a new name encapsulating an existing concept that aims at making spatial predictions using generalized regression analysis.

As a second order quadratic function, with interactions, was chosen for the summer log drying model it is important that predictions using this regression should not be extrapolated beyond the 24 week duration of the study.

The subjective predictions were compared with SAPS II predictions using logistic regression analysis and receiver operating characteristic curve (ROC) measurement, as well as sensitivity and specificity analysis for each group of participants.

C-index values for the 1000 test data sets derived from the TRANSBIG data were calculated based on predictions using Cox regression models fitted to the corresponding training set.

BayMiR infers miRNA activity levels based on the expression profiles of its putative targets (predicted on the basis of conserved seed matches) and then it refines these target predictions using the regression model.