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The finite-strain model is linearized into the small-strain regime preserving the materially non-linear feature.
As already mentioned, training a supervised classifier with a small number of samples (five controls versus four pain subjects) in order to infer a model is risky, and it could be further argued that the use of SVM for classification in the reduced linearized feature-extracted space is excessive for this purpose.
As an example, consider incorporating the object's perimeter P and area A. For a given object, both features are related nonlinearly by A ~ P. Hence, it can help a linear classifier to adapt to this feature vector when the object area is incorporated as A, as the former nonlinear correlation of both features is thus linearized.
For all other thermal generation units, nonlinear production costs are linearized using a piecewise linear production curve, and linked to different fuel prices and their corresponding net heat rates (switch fuel feature).
In the current study, we extend the analysis to test whether the diagnostic accuracy for HAND of the MoCA might be improved with a scoring methodology that produces linearized units of cognitive ability, a scoring feature of true 'measures'measures
An important feature of the present formulation for the diffusion reaction problem is that the reaction term is linearized during the course of solution.
WPN25-sfGFP were purified, linearized and analysed by PFGE.
pKO-AMA1 was linearized with PstI before transfection.
Resulted nonlinear model is linearized.
The model is then linearized.
This vector was subsequently linearized with PmeI and gel-purified.
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