A novel field learning algorithm for dual imbalance text classification
FSKD'05 Proceedings of the Second international conference on Fuzzy Systems and Knowledge Discovery - Volume Part II
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To avoid low quality problem caused by low quality data, this paper introduces an inexactfield learning approach which derives rules by working on the fields of attributes with respect to classes, rather than on individual point values of attributes. The experimental results show that field learning achieved a higher prediction accuracy rate on new unseen test cases which is particularly true when the learning is performed on large low qualitydata.