Mining Needles in a Haystack: Classifying Rare Classes via Two-Phase Rule Induction
Summary: Two-phase rule induction for rare-class learning: Phase I aims for high recall with broad-support rules; Phase II prunes false positives to improve precision. Synthetic models show when RIPPER and C4.5rules falter; on real intrusion data, the method yields balanced recall–precision comparable or superior. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Mahesh V. Joshi
- 2. Ramesh C. Agarwal
- 3. Vipin Kumar
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