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The latter approach is data- driven, where measured data from a given state condition is compared to the baseline or reference condition.
The proposed approach is data driven without considering classification standard of different risk levels, and thus provides a more reasonable and objective result.
The basis of the approach is data on security incidents from a real large-scale production environment at the National Center for Supercomputing Applications (NCSA) at the University of Illinois at Urbana-Champaign (UIUC).
The first step in the proposed approach is data acquisition using a relay feedback experiment and the second step is step response estimation using frequency sampling filters.
In addition, this approach is data intensive and requires significant effort in collecting and processing the related data and calibrating the corresponding models [8].
The approach is data driven and has rarely been applied in the SSA region.
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The new approach is data-intensive.
Because this approach is data-driven, it was essential to minimize the case search times.
Compared with the existing results, the proposed approach is data-based.
Although especially the MAGT model had excellent predictive performance, it should be acknowledged that our approach is data-driven and subject to the data limitations22,87.
An alternative approach is data-driven techniques that are based entirely on analysis and extrapolation of observations.
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