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What is Classif ication Error

Handbook of Research on Text and Web Mining Technologies
Error produced by incorrect classifications, which consists of two types: correct negative (wrongly classify an item belong to one class into another class) and false positive (wrongly classify an item from other classes into the current class)
Published in Chapter:
Image Classification and Retrieval with Mining Technologies
Yu-Jin Zhang (Tsinghua University, Beijing, China)
Copyright: © 2009 |Pages: 15
DOI: 10.4018/978-1-59904-990-8.ch006
Abstract
Mining techniques can play an important role in automatic image classification and content-based retrieval. A novel method for image classification based on feature element through association rule mining is presented in this chapter. The effectiveness of this method comes from two sides. The visual meanings of images can be well captured by discrete feature elements. The associations between the description features and the image contents can be properly discovered with mining technology. Experiments with real images show that the new approach provides not only lower classification and retrieval error but also higher computation efficiency.
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