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Few examples of statistical and computational intelligence tools for data reduction in SoS include the PCA, clustering, fuzzy-logic, neuro-computing, and evolutionary computing, such as genetic algorithms, and Bayesian networks.
We have used well-established tools for data reduction and performance measurement to investigate the behaviour of these platforms for the complicated access patterns of real-life Radio Astronomy data reduction.
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The rough set theory (RST), which has recently become well known as a data-mining technique, is a good tool for data reduction in qualitative analysis.
Combining LCA with CA provides researchers a powerful tool for data reduction analysis.
Approaches to analyze mass spectral data using unsupervised and supervised data mining operations would greatly benefit from tools that effectively allow for data reduction without losing important diagnostic information.
Following data collection, tools for spectral alignment and peak picking were used for data reduction.
This allows for data reduction.
CATPCA is often used for data reduction.
There are two modes for data reduction, i.e., 'sum' reduction mode and 'skip' reduction mode.
Probabilistic models were introduced for data reduction.
Access to software tools for interactive data reduction, visualisation and analysis during a neutron scattering experiment enables instrument users to make informed decisions regarding the direction and success of their experiment.
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