What makes categories difficult to classify?

In this paper, we try to predict which category will be less accurately classified compared with other categories in a classification task that involves multiple categories. The categories with poor predicted performance will be identified before any classifiers are trained and additional steps can...

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Bibliographic Details
Main Authors: SUN, Aixin, LIM, Ee Peng, LIU, Ying
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2009
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Online Access:https://ink.library.smu.edu.sg/sis_research/488
https://ink.library.smu.edu.sg/context/sis_research/article/1487/viewcontent/What_makes_categories_difficult_to_classify_a_stud.pdf
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Institution: Singapore Management University
Language: English
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Summary:In this paper, we try to predict which category will be less accurately classified compared with other categories in a classification task that involves multiple categories. The categories with poor predicted performance will be identified before any classifiers are trained and additional steps can be taken to address the predicted poor accuracies of these categories. Inspired by the work on query performance prediction in ad-hoc retrieval, we propose to predict classification performance using two measures, namely, category size and category coherence. Our experiments on 20-Newsgroup and Reuters-21578 datasets show that the Spearman rank correlation coefficient between the predicted rank of classification performance and the expected classification accuracy is as high as 0.9.