A Fuzzy Adaptive Multi-Population Parallel Genetic Algorithm for Spam Filtering

Provided by: AICIT
Topic: Security
Format: PDF
Now-a-days, e-mail is one of the most inexpensive and expeditious means of communication. However, a principal problem of any internet user is the increasing number of spam, and therefore an efficient spam filtering method is imperative. Feature selection is one of the most important factors, which can influence the classification accuracy rate. To improve the performance of spam prediction, this paper proposes a new Fuzzy Adaptive Multi-population parallel Genetic Algorithm (FAMGA) for feature selection. To maintain the diversity of population, a few studies of multi-swarm strategy are reported, whereas the dynamic parameter setting has not been considered further.

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