Sentence examples for popular regression from inspiring English sources

Worth the Risk: Curtis Granderson is a popular regression pick for 2012 after his monster season in 2011 when he reached career highs in runs, home runs and runs batted in.

Two popular regression methods are SVR (Smola and Schölkopf, 2004) and LASSO regression (Tibshirani, 1996).

The generalized singular value decomposition (GSVD) is a popular regression framework used in joint analysis.

6 This article focuses on ridge and lasso, two popular regression methods that can be used to alleviate the problem of model overfitting and are recommended in the TRIPOD checklist for developing and validating prediction models.

Least squares regression [ 49] and partial least squares (PLS) regression [ 50] are popular regression techniques.

For comparison purposes, we implement the popular Cox regression with group LASSO (G L1Cox), since there is no software available in the literature.

Simulation study based on real data from the HapMap project were used to assess the performance of our PLS-based MLAS as well as other popular multilinear regression-based MLAS approaches under various scenarios, considering genetic effects and linkage disequilibrium structure of candidate genetic regions.

The kLog framework can be applied to tackle the same range of tasks that has made statistical relational learning so popular, including classification, regression, multitask learning, and collective classification.

The random forests (RF) [ 29] is a popular classification and regression algorithm based on an ensemble of many classification/regression trees combined with a bootstrap sample out of the original dataset.

We consider five indicators of building performance and eight test problems for the comparison six popular metamodeling techniques – linear regression with ordinary least squares (OLS), random forest (RF), support vector regression (SVR), multivariate adaptive regression splines, Gaussian process regression (GPR), and neural network (NN).

Regression discontinuity studies have typically used linear regression models, popular among economists.