Sentence examples for uses the linear combination from inspiring English sources

The error rate on the test data is treated as the e0 estimator, while the.632 bootstrap also takes the training error into consideration, and uses the linear combination of 0.368∗ ε + 0.632∗ e0 as the estimated error rate, where ε is the training error.

Then using the linear combination method and the constraint penalty function method, a deterministic single-objective and non-constraint optimization problem is formulated in terms of a penalty function.

Therefore, we use the linear combination in the log domain, which is equivalent to the product in equation (21).

For example, Niblack [19] and Sauvola et al. [27] used the linear combination of local mean and standard deviation for the thresholds.

PR spectra were fitted using the linear combination of several Aspnes' TDFFs [11], expressed as: Δ R R = Re ∑ j = 1 n A j e − i φ j E − E gj + i Γ j − m j + f j E, (4).

Keinan, S; Hu, X; Beratan, DN; Yang, W, Designing molecules with optimal properties using the linear combination of atomic potentials approach in an AM1 semiempirical framework., The Journal of Physical Chemistry A, vol. 111 no. 1 (January, 2007), pp. 176-181, [abs] [abs].

Motivated in part by recent advances in the hardware and sensor information processing, such as solid state transmission and digital arbitrary waveform generators, in modern radar systems, any polarization on either transmission or reception can be synthesized by using the linear combination of the H and V components.

The optimization of the four nucleosides is performed using the linear combination of atomic orbital basis SIESTA code[15, 16], implementing the density functional theory (DFT) with the generalized gradient approximation (GGA) and the function of Perdew, Burke, and Ernzerh known as PBE[17, 18].

The values of Y1 and Y2 were subsequently computed for the healthy controls using the "linear combination" rule derived for the CD patients.

Therefore, given a set of gene expression microarray data, we attempt to construct a linear regression model for each microarray to predict the expression levels for each gene using the linear combination of the gene's motif scores.

Since the multi-locus GRS in our model is constructed using the linear combination of the genetic risk alleles, weighted by their genetic effects that are estimated from the univariate models, similar to the multivariate regression model using multiple predictors, the linear combination of such effects may over fit the data and cause inflated type I error.