of interest. This algorithm provides us with a new class of loss-based cross-validated algorithms in prediction of …

When trying to learn a model for the prediction of an outcome given a set of covariates, a statistician has many … learners. Motivated by this use of cross validation, we propose a new prediction method for creating a weighted combination of … in prediction which uses V-fold cross-validation to select weights to combine an initial set of candidate learners. In …

a prediction of viral replication capacity based on an entire mutant/non-mutant sequence profile. This is a loss … estimators in the prediction of a univariate outcome by minimizing an empirical risk. These methods are two separate techniques …

When trying to learn a model for the prediction of an outcome given a set of covariates, a statistician has many … learners. Motivated by this use of cross validation, we propose a new prediction method for creating a weighted combination of … in prediction which uses V-fold cross-validation to select weights to combine an initial set of candidate learners. In …

of interest. This algorithm provides us with a new class of loss-based cross-validated algorithms in prediction of …

a prediction of viral replication capacity based on an entire mutant/non-mutant sequence profile. This is a loss … estimators in the prediction of a univariate outcome by minimizing an empirical risk. These methods are two separate techniques …