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Thus Boorse, who argues for the value-neutral view of classification, suggests that evolutionary theory can tell us what conditions are healthy.
They describe some of the major statistical contributions to the areas of machine learning and computational linguistics, from the point of view of classification and clustering algorithms.
From the point of view of classification, there are three broad approaches for calculation of SIF—(1) Analytical, (2) Numerical, and (3) Experimental approaches.
This view of classification is, however, flawed.
It selects the bands based on pattern recognition principles for classification tasks, that is, in this case the band selection is treated as a feature selection problem in pattern recognition, using the response of the chosen classifier combined with the SFFS strategy to select the subset of bands that are more relevant from the point of view of classification performance.
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Those patterns can be interpreted in view of the classification methods and objectives for which each classification has been developed.
The plots from Figure 7 give an overall view of this classification problem on the annotated subset.
The plots in Figure 8 give an overall view of this classification problem on the real subset.
In view of such classification, the analysis carried out on cable linear modal properties shows the emergence of new dynamic features such as additional hybrid modes and internal resonances.
In the present study, we investigate six of them, which have already been proposed by various authors in view of site classification (see, for instance, Castellaro et al. 2008; Cadet et al. 2012; Pitilakis et al. 2012, 2013), and provide information on the stiffness and/or thickness of soil columns.
An overall view of the classification of FGROUP entries is summarized in Figure 1 (the complete set defined to date is available at http://bisscat.org/fgroup.html).
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