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We therefore minimize the squared scaled error sum E tA, ΔTA2) = Σi ei2(1+αi2) which is a weighted least squares problem in the variables (tA, ΔTA2) [79] (Fig 13B).
Landmark configurations are translated, scaled and rotated so as to minimize the squared, summed distances between the corresponding landmarks of each individual and the mean [ 26].
As ordinary least squares, ridge regression also aims to minimize the squared error term, but adds a quadratic regularization penalty on large values of the weight vector β.
This model can be represented by: y - β0 + β1 x1 +...+ β p x p Ordinary least-squares models estimate the coefficients to minimize the squared sum of residuals.
These laws are developed on the basis of a gradient approach to minimize the squared augmented error.
The room is modeled with the image method as a rectangular enclosure with a stationary point source; the active barrier is set up by an array of loudspeakers and error microphones and is meant to minimize the squared sound pressure on a wall with the use of a decentralized control.
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We introduce a new minimization that simultaneously minimizes the squared flows and the squared differences between flows.
For nonlinearly separable classes linear classifiers were optimally designed, for example, by minimizing the squared error.
The optimal power distribution can be obtained by minimizing the squared η2 in (23) with respect to λ under the constraints that (28).
To find a best match, the observed foundress numbers and the simulated foundress numbers are binned in ranges: 1 3, 4 6, >6, with the best match being that which minimizes the squared deviations between observed and simulated distributions.
The Jenks method minimized the squared deviations of the class means and set boundaries where relatively large spaces between exposure metric values occurred.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com