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Partial least square (PLS) may represent a solution where such multivariate methods fail.
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Again these methods fail to produce general MeSH terms.
By comparison, conventional methods fail at one or both.
This can help if above methods fail.
These methods failed in separating levels 6 and 4.
All methods failed to detect very low-intensity infections.
It is shown that the multivariate uncertainty analysis method fails when the perturbations are relatively large and/or the output distribution is non-Gaussian, and therefore the Monte-Carlo analysis should be used in the general case.
In this case, multivariate analysis using an explorative and visual method, failed to identify homogeneous "clouds of objects" and seems to confirm the previously stated thesis.
However, existing pattern recognition method failed to capitalize on the nature of multivariate associations between the extracted fault features.
Multivariate methods should, therefore, be considered instead.
Data were analyzed using univariate and multivariate methods.
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