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Adaptive binning overcomes the data set size and multidimensional extensibility issues to focus analysis on the most informative regions of the data; however, sample comparison is control-specific in probability binned chi-square (PB-χ) tests, making the test result unsuitable as a true (linear) metric for directly comparing multiple samples.
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Regularization proved to be a valid method to overcome the data scarcity.
Using predictions for large datasets (e.g. compound libraries) allows us to overcome the data limitation problem.
While Google and Microsoft can use their deep pockets to keep up on the innovation front, it's harder to overcome the data disparity.
Microsoft describes it as a "ruggedized, tamper-resistant and human-manageable applications that will help organizations overcome the data transfer barriers that can block productivity and slow innovation".
Auxiliary data sources, like videos, are thus necessary to overcome the data deficiency in photo collections and to obtain more complete models.
The challenge in using these archives is overcoming the "data deluge" that makes retrieving specific recordings from a large database difficult.
To deal with large scale power systems, an additional device called voltage measuring unit (VMU) is introduced in [22, 23] to overcome the data quality issue of PMUs.
To overcome the data conversion problem of complex geometrical, the calculation model of ground movement can be established within the GIS.
To overcome the data sparse problem in collaborative filtering, structural similarity between users [18] and objects based on bipartite network model [10] were proposed.
A weighted least squares (WLS) method is designed to estimate the parameters of plant, which could overcome the data uncertainty problem caused by delays and dropout.
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