Autonomous document classification for business
AGENTS '97 Proceedings of the first international conference on Autonomous agents
Evaluating cost-sensitive Unsolicited Bulk Email categorization
Proceedings of the 2002 ACM symposium on Applied computing
Genetic Programming and Evolvable Machines
A Comparative Study on Feature Selection in Text Categorization
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Non-destructive Depth-Dependent Crossover for Genetic Programming
EuroGP '98 Proceedings of the First European Workshop on Genetic Programming
"In vivo" spam filtering: a challenge problem for KDD
ACM SIGKDD Explorations Newsletter
An evaluation of statistical spam filtering techniques
ACM Transactions on Asian Language Information Processing (TALIP)
Evolving rules for document classification
EuroGP'05 Proceedings of the 8th European conference on Genetic Programming
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Support vector machines for spam categorization
IEEE Transactions on Neural Networks
A survey on the application of genetic programming to classification
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Information Sciences: an International Journal
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In this paper we apply multiobjective genetic programming to the cost-sensitive classification task of labelling spam e-mails. We consider three publicly-available spam corpora and make comparison with both support vector machines and naïve Bayes classifiers, both of which are held to perform well on the spam filtering problem. We find that for the high cost ratios of practical interest, our cost-sensitive multiobjective genetic programming gives the best results across a range of performance measures.