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Generate state-level alignments on the training data set using a bootstrap model set.
The full steps for growing the DTs and training the DTAMs are as follows: 1. Generate state-level alignments on the training data set using a bootstrap model set. 2.
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Cost data comparisons between the groups will be made using a bootstrap regression model (using 10,000 repetitions).
Therefore, we first evaluated all LUR models using a bootstrap approach to determine the sensitivity of model prediction and parameter estimates to monitor sampling.
We validated each model using a bootstrap method (10,000-iteration) and reported the bootstrap bias-corrected AUCs with 95% bootstrap confidence interval (CI) (15).
The calibration (Hosmer Lemeshow statistic) and discrimination (area under the curve, AUC) were calculated, and the model internally validated using a bootstrap methodology [17].
The transcriptomic data was used to identify statistically significantly expressed gene models using a bootstrap-style approach, and these expressed genes were mapped to specific metabolic pathways.
Martin and Roberts (2006) implemented model averaging using a bootstrap-based procedure and showed that it is competitive with BMA in that context.
The mediation model was tested using a bootstrapping method.
Different age models, CAM and MAM-3, were used to establish palaeodose and the robustness of these age models was tested using a bootstrapping technique.
For learning evolutionary prediction model, we use a bootstrap sampling [26] with a sample size of 85 % and 10,000 replications.
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