Classification of Style-Constrained Pattern-Fields
نویسندگان
چکیده
In some classification tasks, all patterns in a field, such as digits in a ZIP-code image, originate from the same, but unknown, source (writer/print style). The class-conditional feature distributions depend on the source of the patterns. Several sources may share the same distribution, or style. The style-conditional distributions are estimated from the training set. The optimal field-classifier computes the classconditional field-feature-probabilities as the sum of classand-style-conditional field-feature-probabilities, weighted by the prior probabilities of the styles. We compare the decision regions and error rates of style-weighted classification with both conventional singlet and top-style classification in a minimal family of examples, and discuss some related practical considerations.
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