In Section 4 we show that any PMD in which a coplane is not the intersection of two hyperplanes is an extension of a projective plane. |
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Its goal is to find hyperplanes in the attribute's space in order to maximize the margin between instances that belong to distinct classes. |
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It then employs hyperplanes to separate positive data from the negative ones. |
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In their basic form, SVMs attempt to perform classification by constructing hyperplanes in a multidimensional space that separates the cases of different class labels. |
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