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Once the optimal feature and its threshold are found by minimizing the weighted error, the next step is to update the weights.
We derive rigorous weighted error estimates which provide more precise convergence rate for problems with singularities at boundaries.
For this purpose, an improved L1 weighted error function is formulated in frequency domain, and minimized through CS, PSO and ABC respectively.
In the presence of constraints, the objective function is a weighted error function between the desired optimal and candidate voltage control signals.
This paper presents a novel discrete choice model formulation: the spatially weighted error correlation (SWEC) logit model for spatial location choices.
Here, we demonstrate that considering the sum of a higher weighted error than the sum of squared errors leads the HNN classifier to go more deeply in the energy landscape.
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The RMSE was calculated as the square root of the sum of the squared weighted errors between the observed daily cases and the fitted model; the weight being the fitted value,.
Eventually, employing the NURBS technique and skinning method, the NURBS DTM, which represents a NURBS surface and satisfies the requirement after precision assess with weighted errors, is reconstructed with the intermediate data.
where E w0 is the weighted localization error associated with the reference model, and E wj (j=1,…,3) are the corresponding weighted errors in localization using the models after the outlier removal methods applied.
Different ways to compute the errors allowed in the approximate patterns (restricted errors, alphabet range weighted errors and pattern length adaptive errors) can also be used.
The proposed e-CCC-Biclustering algorithm can be modified in order to cope with the three different kinds of errors described below: restricted errors, alphabet range weighted errors, and pattern length adaptive errors.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com