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Methods for data reduction or compression must be included.
Systematic methods for data reduction have been developed for the dual rotating-compensator ellipsometer in the PC1r ω1)SC2r(ω2)A configuration, where P, C1r ω1), S, C2r ω2), and A represent the polarizer, first rotating compensator, reflecting sample, second rotating compensator, and analyzer, respectively.
Principal component analysis (PCA) is one of the most commonly used chemometric methods for data reduction and exploratory analysis of high-dimensional data sets.
Data analysis will include descriptive statistics and graphical representations and methods for data reduction, classification techniques and psychometric analysis, before moving to bi-variate and multivariate analysis.
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The coding system and method for data reduction employed varied between the two studies; the details are included under the results for each study.
Likewise, data preprocessing, dimension reduction, data mining, and machine learning methods are useful for data reduction at different levels in big data systems.
Although the application of these methods is convenient for data reduction, the trade-off between energy consumptions in local processing with raw data transmission is a key challenge that is needed to be considered.
Compression-based methods are suitable candidates for data reduction in terms of size by preserving the whole data streams.
New video techniques to study meteor spectra started to be used in the early 1970s (Hemenway et al. 1971), as well as new methods and TV processes for data reduction, described by Millman and Clifton (1975), Borovicka and Bocek (1995) and Zender et al. (2004).
Spatial DFA gave best results for data reduction method.
The study demonstrated that text mining methodologies such as topic modeling provide an alternative method compared to traditional means for data reduction in toxicogenomics, enhancing researchers' capabilities to interpret biological information.
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