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In addition, data mining methods need to overcome sparsity, heterogeneity, uncertainty, and incompleteness of Big Data as well.
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The dual mining method eliminates the need to develop a specific representation language for biomedicine, to elicit user's knowledge.
Therefore, interpretation of the results obtained from Raman and IR spectroscopy is difficult and to overcome these intricacies and for deeper insight we need to employ various data mining methods.
Such wealthy information in these data needs to be extracted and transformed to useful knowledge by various data mining methods.
A brain mapping study needs several enabling techniques, including 3D image registration (alignment), neurite tracing, neuronal pattern classification, visualization and mining methods (Peng, 2008).
This precludes large-scale, highly mechanized mining methods.
New mining methods are discovered, as are processes that make more economical use of lesser grades.
Every year, new pesticides, fishing technologies, mining methods, techniques for processing trees are developed.
In this paper, we review some recent data mining methods for (1) mining tensor imaging data; (2) mining brain networks; and (3) mining multi-view feature vectors.
In underground coal mines, surface subsidence induced by different mining methods are very different.
What methods need to be used?
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