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In this section, we explain the data reduction method.
Spatial DFA gave best results for data reduction method.
The Bayesian fusion along with traffic sampling is employed as a data reduction method.
The satisfactory performance of both the proposed TDR waveguides and data reduction method was experimentally validated.
The computational cost by the Greedy method, the multi-level data reduction method and the developed method, are theoretically compared.
A more consistent data reduction method is desired to calculate relative spinal motion (range of motion) from raw marker data.
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The similarity-based big data reduction methods are good choice for network extraction and reduction.
This section presents the data reduction methods being applied in big data systems.
These adoptions open new research avenues for interdisciplinary research and develop novel big data reduction methods.
In general, compression-based data reduction methods are convenient for reducing volume.
In this study, we presented a detailed discussion of these data reduction methods.
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