A decision-theoretic roguth set model
Methodologies for intelligent systems, 5
Classifying news stories using memory based reasoning
SIGIR '92 Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval
Variable precision rough set model
Journal of Computer and System Sciences
Advances in the Dempster-Shafer theory of evidence
Key concepts in model selection: performance and generalizability
Journal of Mathematical Psychology
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
BoosTexter: A Boosting-based Systemfor Text Categorization
Machine Learning - Special issue on information retrieval
Machine Learning
Decision-theoretic rough set models
RSKT'07 Proceedings of the 2nd international conference on Rough sets and knowledge technology
Probabilistic model criteria with decision-theoretic rough sets
Information Sciences: an International Journal
A new formulation of multi-category decision-theoretic rough sets
RSKT'11 Proceedings of the 6th international conference on Rough sets and knowledge technology
Expert Systems with Applications: An International Journal
Decision-Theoretic rough sets with probabilistic distribution
RSKT'12 Proceedings of the 7th international conference on Rough Sets and Knowledge Technology
A Multiple-category Classification Approach with Decision-theoretic Rough Sets
Fundamenta Informaticae - Rough Sets and Knowledge Technology (RSKT 2010)
A comparison study of cost-sensitive classifier evaluations
BI'12 Proceedings of the 2012 international conference on Brain Informatics
Projected-prototype based classifier for text categorization
Knowledge-Based Systems
Incorporating logistic regression to decision-theoretic rough sets for classifications
International Journal of Approximate Reasoning
Multi-class decision-theoretic rough sets
International Journal of Approximate Reasoning
On an optimization representation of decision-theoretic rough set model
International Journal of Approximate Reasoning
Cost-sensitive three-way email spam filtering
Journal of Intelligent Information Systems
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Many classification techniques used for identifying spam emails, treat spam filtering as a binary classification problem That is, the incoming email is either spam or non-spam This treatment is more for mathematical simplicity other than reflecting the true state of nature In this paper, we introduce a three-way decision approach to spam filtering based on Bayesian decision theory, which provides a more sensible feedback to users for precautionary handling their incoming emails, thereby reduces the chances of misclassification The main advantage of our approach is that it allows the possibility of rejection, i.e., of refusing to make a decision The undecided cases must be re-examined by collecting additional information A loss function is defined to state how costly each action is, a pair of threshold values on the posterior odds ratio is systematically calculated based on the loss function, and the final decision is to select the action for which the overall cost is minimum Our experimental results show that the new approach reduces the error rate of classifying a legitimate email to spam, and provides better spam precision and weighted accuracy.