Buddeewong, Supaporn and Kreesuradej, Worapoj (2005) A new association rule-based text classifier algorithm In: 17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05), 2005-11-16, Hong Kong, China.
This paper proposes a new association rule-based text classifier algorithm to improve the prediction accuracy of association rule-based classifier by categories (ARC-BC) algorithm. Unlike the previous algorithms, the proposed association rule generation algorithm constructs two types of frequent itemsets. The first frequent itemsets, i.e. L<sub>k</sub> contain all term that have no an overlap with other categories. The second frequent itemsets, i.e. OL<sub>k</sub> contain all features that have an overlap with other categories. In addition, this paper also proposes a new join operation for the second frequent itemsets. The experimental results are shown a good performance of the proposed classifier
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ระบบ อัตโนมัติ
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2021-09-09 23:53:47
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2021-10-05 06:26:29