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Hence, the colored bars show the minimum, maximum, and mean classification rates for all DC methods among the different DC methods used.
The differently colored bars show the minimum, maximum, and mean classification rates for all DC methods among the different interpolation methods used.
In order to check the effect of normative inversion on unaffected controls, we used multi-folded cross validation, employing closest mean classification to determine discriminating differences between 387 controls and their inverted forms.
Table 3 presents the RotBoost mean classification accuracy against the considered 8 gene datasets when transformation matrix is chosen to be either PCA or ICA where the values following "±" denote the related standard deviations.
Finally, to detect any possibility of facial inversion producing features similar to those of Williams Beuren syndrome, we also tested closest mean classification of normatively inverted controls in a control-Williams Beuren syndrome control-Williams Beuren
Mean classification accuracy for all descriptors on the Brodatz dataset.
Mean classification accuracy for all descriptors on the UIUC dataset.
Mean classification grade in parenteral intoxications was 2.3.
Mean classification accuracy for all descriptors on the Kylberg dataset.
Mean classification accuracy for all descriptors on the Virus dataset.
Table 2 Mean classification accuracy at θ=0°.
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