Using One-Class SVM with Spam Classification | ||
Iraqi Journal of Science | ||
Article 1, Volume 57, Issue 1, February 2016, Pages 501-506 | ||
Authors | ||
Inas Ali; Sumaya Saad; Safa Ahmed | ||
Abstract | ||
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. | ||
Keywords | ||
gain ratio; Spam; SVM | ||
Statistics Article View: 177 PDF Download: 156 |