Using one-class SVM with spam classification

Abstract EN

Support Vector Machine (SVM) is supervised machine learning technique which has become a popular technique for e-mail classifiers because its performance improves the accuracy of classification.

The proposed method combines gain ratio (GR) which is feature selection method with one-class training SVM to increase the efficiency of the detection process and decrease the cost.

The results show high accuracy up to 100 % and less error rate with less number of feature to 5 features.