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Spam Filtering: the Influence of the Temporal Distribution of Training Data
Anton Bryl
249 - 250
Frontiers in Artificial Intelligence and Applications
Volume 142: STAIRS 2006
Abstract

The great number and variety of learning-based spam filters proposed during the last years cause the need in many-sided evaluation of them. This paper is dedicated to the evaluation of the dependence of filtering accuracy on the temporal distribution of training data. Such evaluation may be useful for organizing effective training of the filter.

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