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The conceptual block diagram of the radius selection algorithm using bootstrap method is shown in Figure 2 and the detailed steps are described below.
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Bootstrap resampling methods were shown in [ 24] to have more power than array permutation methods in simulated and real data sets, and expansions beyond the existing resampling approaches are worthy of investigation.
Also, a bootstrap method is proposed to obtain critical values.
Bootstrap method is a nonparametric method which requires no assumptions about the data distribution.
A bootstrap method is also discussed, and its performance is evaluated through simulations.
A bootstrap method is used to evaluate the stability of the solution.
Unfortunately, no bootstrap method is available for rearrangement studies.
Bootstrap methods have been shown to have good properties when compared with parametric methods[2 4].
In this paper, the bootstrap method was used to estimate the frequency of a signal.
Bootstrap method was utilised to calculate the CIs for AUC.
The performance comparison of the bootstrap aggregated neural networks and bootstrap aggregated ELM is shown in Table 1.
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