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Neural network metaparameters are often optimized by a "bootstrapping" process [13].
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Such a bootstrapping process is intended to exclude transformations that are based on non-reliable predictions.
It is, thus, a bootstrapping process that has no end in sight.
SNAP was trained in a bootstrap process as described below.
SE was estimated by a bootstrap procedure (1000 replicates).
Standard errors were obtained by a bootstrap procedure (1000 replicates).
In both cases shown in the ROC plots, the ROC analyses (Figs. 2 and 3c) yielded a significant AUC, indicating the ROC curve was not affected significantly by the bootstrapping process and demonstrating the robustness of our 17-urine-peptide biomarker panel in discriminative analyses.
Finally, we present a reference bootstrap process for a reflective system and Hazelnut, its implementation for bootstrapping the Pharo Smalltalk-inspired system.
During the bootstrapping process, the CMP will establish a binding between the DHoA and LCoA.
We further estimated the confidence intervals of α by the nonparametric bootstrapping method described in [ 31], with the bootstrapping process repeated 1000 times.
This bootstrapping process continues over a selected number of iterations, and the cross domain classifier learned in the bootstrapping process is now available to predict target samples.
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