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https://scholarhub.balamand.edu.lb/handle/uob/1852
Title: | Different PCA scenarios for email filtering | Authors: | Dagher, Issam Antoun, Rima |
Affiliations: | Department of Computer Engineering | Keywords: | Ham Spam PCA SVM Bayes |
Issue Date: | 2016 | Part of: | International journal of computers and applications | Volume: | 38 | Issue: | 1 | Start page: | 41 | End page: | 45 | Abstract: | Improving email filtering (Ham vs. Spam emails) is a very important process. The objective of this paper is to increase the filtering accuracy and to decrease the processing time. It discusses different scenarios for Principal Component Analysis-Document Reconstruction (PCADR) classifier implemented for email filtering process The study highlights on the variation in the accuracy of a PCADR classifier with respect to the variation in feature preprocessing. Four scenarios were considered:{09} Scenario 1: Ham and Spam classes are represented with different features.{09} Scenario 2: Ham and Spam classes are represented with same features.{09} Scenario 3: Ham and Spam classes are represented with common terms.{09} Scenario 4: Ham and Spam classes are represented with common Features and Characteristic terms. Different experiments were done using a public corpus extracted from the University of California-Irvine Machine Learning Repository. Different training and test sets were used. A comparison of PCADR with Support Vector Machine and Bayes detector was done to prove its superior behavior. |
URI: | https://scholarhub.balamand.edu.lb/handle/uob/1852 | DOI: | 10.1080/1206212X.2016.1218237 | Ezproxy URL: | Link to full text | Type: | Journal Article |
Appears in Collections: | Department of Computer Engineering |
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