Sentence examples for data reduction approaches from inspiring English sources
Alternative data reduction approaches resulting from this capability of over-determination are shown through numerical simulations to have different performance characteristics under non-ideal experimental conditions.
CDE experienced higher noise levels than expected on-orbit, triggering the need for new laboratory experiments, as well as the development of new data reduction approaches.
To mention just a few, these include algorithms for processing the data more time and space efficiently (Langmead et al., 2009; Li and Durbin, 2009a; Li et al., 2009b) as well as data reduction approaches that aim to retain only the scientifically relevant and non-redundant information from NGS projects rather than everything (Leinonen et al., 2010).
Further a focused data reduction approach was employed to choose a subset of enriched compounds based on "Drug likeness" and "Similarity-based" methods.
In this work, a J-integral-based data reduction approach was used for fracture characterisation of a ductile two-component epoxy adhesive with steel adherends under mixed-mode loading.
This data reduction approach may assist investigators who wish to quantify functional limitations in RA.
MDR is a data reduction approach, designed to detect and characterize high-order interactions in case-control studies.
A limitation of many of these methods is the fact that they use a data reduction approach which makes it difficult to select a minimal set of markers.
The original MDR algorithm was designed as a data reduction approach to identify multi-locus genotype combinations that are associated with high or low risk of disease [ 34].
We compared our proposed method to another data reduction approach, namely, principal component analysis (Weller et al. 1996), and showed with real data that our method outperformed it in terms of statistical power.
Because of the data reduction approach used for index construction (principal components analysis (PCA), discussed in detail below), and the statistical assumptions implied by this method, variables were assessed for normality.
