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However, a lot of valuable information may be lost by data reduction using shift tables only.
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To do this, we first simplified the analysis by performing data reduction using PCA (principal component analysis), 24 a method that creates a visualization of different clusters in two- or three-dimensional space, allowing the highest variations to be determined.
We therefore performed necessary data reduction using genefilter [ 10] by focusing only on 3,203 RefSeq-annotated genes variably expressed across samples (minimum interquantile range of 1.0 on log2 scale).
The technique also decreases the number of adjustable parameters to be determined by data reduction, by using an efficient experimental and mathematical regularization strategy to find their values.
A data-driven model based optimization on the synthesis of nanosized silver particles by chemical reduction using formaldehyde in aqueous solution was studied in this work.
The results show that the proposed PCA-Gabor approach performs better than either the PCA alone or the standard MP data reduction methods, by using the smallest amount of ERP data variance to produce the strongest statistical separation between experimental conditions.
The EXAFS (Extended X-ray Absorption Fine Structures) data reduction was done using a series of programs developed by Michalowicz [29] based on standard procedures [30].
Data reduction was performed using DOSC, WPT and PLS algorithm.
Data reduction was performed using the Glitter software.
Data reduction was performed using customised software (Propero, Odense, Denmark).
Data reduction was performed using StatLIA Enterprise 3.2 (Brendan Technologies).
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