Spam filtering using bayesian technique based on independent feature selection

Bayesian technique is one of the classification techniques which can be applied to a certain problem domain such as classification task. Therefore, this technique had been chosen to conduct a classification task with emails dataset where the emails are comprised of spam and non spam emails. Bayesian...

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Main Author: Mohamad, Masurah
Format: Thesis
Language:English
Published: 2006
Subjects:
Online Access:http://eprints.utm.my/4066/
http://eprints.utm.my/4066/1/MasurahMohamadMFSKSM2006.pdf
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author Mohamad, Masurah
author_facet Mohamad, Masurah
author_sort Mohamad, Masurah
building UTeM Institutional Repository
collection Online Access
description Bayesian technique is one of the classification techniques which can be applied to a certain problem domain such as classification task. Therefore, this technique had been chosen to conduct a classification task with emails dataset where the emails are comprised of spam and non spam emails. Bayesian technique has been applied to observe whether it can produce a good result in spam emails classification or not. Beside, this project also applied Rough set as a comparison technique to classify the spam emails. The classification task is done based on the independent feature selection where only one most occurrence term for each email is chosen as an input to the Bayesian probability. Some of the measurement evaluation had been used to evaluate the classification performance. The measurements are precision, recall, sensitivity, specificity, accuracy and error rate. After the measurements process, these two technique were compared to identify which one of these two techniques is best in classifies spam emails based on the experimental results. The results show that Bayesian technique is good than Rough set technique in classifies spam emails. However the results also indicate that Rough set also suitable for spam filtering problem. Finally, some suggestions were being discussed so that this project can be improved in future work to get a better result compared to the current result which had been retrieved in this project.
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spelling utm-40662018-01-15T04:21:33Z http://eprints.utm.my/4066/ Spam filtering using bayesian technique based on independent feature selection Mohamad, Masurah QA75 Electronic computers. Computer science Bayesian technique is one of the classification techniques which can be applied to a certain problem domain such as classification task. Therefore, this technique had been chosen to conduct a classification task with emails dataset where the emails are comprised of spam and non spam emails. Bayesian technique has been applied to observe whether it can produce a good result in spam emails classification or not. Beside, this project also applied Rough set as a comparison technique to classify the spam emails. The classification task is done based on the independent feature selection where only one most occurrence term for each email is chosen as an input to the Bayesian probability. Some of the measurement evaluation had been used to evaluate the classification performance. The measurements are precision, recall, sensitivity, specificity, accuracy and error rate. After the measurements process, these two technique were compared to identify which one of these two techniques is best in classifies spam emails based on the experimental results. The results show that Bayesian technique is good than Rough set technique in classifies spam emails. However the results also indicate that Rough set also suitable for spam filtering problem. Finally, some suggestions were being discussed so that this project can be improved in future work to get a better result compared to the current result which had been retrieved in this project. 2006-04 Thesis NonPeerReviewed application/pdf en http://eprints.utm.my/4066/1/MasurahMohamadMFSKSM2006.pdf Mohamad, Masurah (2006) Spam filtering using bayesian technique based on independent feature selection. Masters thesis, Universiti Teknologi Malaysia, Faculty of Computer Science and Information System.
spellingShingle QA75 Electronic computers. Computer science
Mohamad, Masurah
Spam filtering using bayesian technique based on independent feature selection
title Spam filtering using bayesian technique based on independent feature selection
title_full Spam filtering using bayesian technique based on independent feature selection
title_fullStr Spam filtering using bayesian technique based on independent feature selection
title_full_unstemmed Spam filtering using bayesian technique based on independent feature selection
title_short Spam filtering using bayesian technique based on independent feature selection
title_sort spam filtering using bayesian technique based on independent feature selection
topic QA75 Electronic computers. Computer science
url http://eprints.utm.my/4066/
http://eprints.utm.my/4066/1/MasurahMohamadMFSKSM2006.pdf