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Rough set approach to spam filter learning.

Glymin, MawuenaFaculty of Graduate Studies and Research, University of Regina2010

regina Repository record for Rough set approach to spam filter learning. (opens in a new tab)

Prediction games : machine learning in the presence of an adversary

Brückner, MichaelUniversität Potsdam

… data. Consider, for instance, the task of email spam filtering where one seeks to find a model which automatically assigns new, previously unseen emails to class spam or non-spam. Building such a predictive model based on observed training inputs (e.g., emails) with corresponding outputs (e.g., …

potsdam-diss Repository record for Prediction games : machine learning in the presence of an adversary (opens in a new tab)

Improving the Prediction Accuracy of Text Data and Attribute Data Mining with Data Preprocessing

CHANDRASEKAR, PRIYANGA2016

… is suggested as the best method to identify the spam emails. The Impact of preprocessing phase on the performance of the Naïve Bayes classifier is analyzed by comparing the output of both the preprocessed dataset result and non-preprocessed dataset result. The test results show that combining …

kennesaw Repository record for Improving the Prediction Accuracy of Text Data and Attribute Data Mining with Data Preprocessing (opens in a new tab)