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Method and computer program product for identifying output classes with multi-modal dispersion in feature space and incorporating multi-modal structure into a pattern recognition system

机译:用于在特征空间中识别具有多模式分散的输出类别并将多模式结构合并到模式识别系统中的方法和计算机程序产品

摘要

A method and computer program product are disclosed for identifying output classes with multi-modal dispersion in feature space and incorporating multi-modal structure into a pattern recognition system architecture. A plurality of input patterns, determined not to be associated with any of a set of at least one represented output class by a pattern recognition classifier, are rejected. The rejected pattern samples are grouped into clusters according to the similarities between the pattern samples. Clusters that contain samples associated with a represented output class are identified via independent review. The classifier is then retrained to recognize the identified clusters as output pseudoclasses separate from the represented output class with which they are associated. The system architecture is reorganized to incorporate the output pseudoclasses. The output pseudoclasses are rejoined to their associated class after classification.
机译:公开了一种方法和计算机程序产品,用于识别特征空间中具有多模式分散的输出类别,并将多模式结构合并到模式识别系统体系结构中。拒绝由模式识别分类器确定与一组至少一个表示的输出类别的任何一个都不相关的多个输入模式。根据模式样本之间的相似性,将拒绝的模式样本分组为群集。包含与表示的输出类别关联的样本的聚类通过独立审核进行标识。然后,对分类器进行重新训练,以将识别出的集群识别为与与之关联的表示的输出类分离的输出伪类。重新组织了系统架构,以合并输出伪类。分类后,输出伪类将重新加入其关联的类。

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