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Pattern Recognition by Matthias Nagel, Matthias Richter, Jürgen Beyerer

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8Classification with nominal features

The techniques we have discussed so far implicitly assume that the feature space is continuous. This means that the classifiers operate on features with an interval scale, ratio scale, or absolute scale (see Section 2.1). However, this is not always the case.

Consider, for example, the classification of plant leaves according to a high level botanical description of (a) the shape of the bud of the plant, and (b) the morphology of the leaf. Both are nominal features, i.e., features without a quantitative meaning and without any ordering. The only meaningful relation is equivalence, that is, it is only possible to tell whether two occurrences of the feature are the same or not. Nominal features are discrete ...

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