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Spatial information is useful to make the classification task stronger (e.g., pupil is surrounded of sclera).
The main purpose of imaging algorithms is to achieve enough resolution to make the classification step easy.
The authors proposed the decomposition of a M-ary subtest into a set of binary tests, represented in a decision tree, to make the classification process simpler.
The fiducial probability output of classification results can make the classification results of the vague samples to be effectively recognized for subsequent processing.
On the other hand, having a very large feature vector will make the classification process slow and is not guaranteed to increase classification accuracy.
It is reasonable to assume that objects drawn from the same class distribution can be grouped together in order to make the classification problem simpler.
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But this has not deterred St. Émilion's leaders from making the classification ever more rigorous.
Moreover, including the volume of HO as a criterion would have made the classification more complex.
This directly makes the classification decision function in the VCA method hard to operate.
Some clutter interference has been removed, making the classification result better.
This makes the classification more consistent with small size of training data.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com