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An Analysis of Case-Base Editing in a Spam Filtering System
[chapter]
2004
Lecture Notes in Computer Science
Because of the volume of spam email and its evolving nature, any deployed Machine Learning-based spam filtering system will need to have procedures for case-base maintenance. Key to this will be procedures to edit the case-base to remove noise and eliminate redundancy. In this paper we present a two stage process to do this. We present a new noise reduction algorithm called Blame-Based Noise Reduction that removes cases that are observed to cause misclassification. We also present an algorithm
doi:10.1007/978-3-540-28631-8_11
fatcat:o2iy3qrowrbldfh3m6ipigcbca