Comparative Study of Gaussian and Nearest Mean Classifiers for Filtering Spam E-mails

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Dr. Upasna Attri
Dr. Upasna Attri
2
Harpreet Kaur
Harpreet Kaur
1 Punjab Technical University, Jalandhar (India)

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The development of data-mining applications such as classification and clustering has shown the need for machine learning algorithms to be applied to large scale data. The article gives an overview of some of the most popular machine learning methods (Gaussian and Nearest Mean) and of their applicability to the problem of spam e-mail filtering. The aim of this paper is to compare and investigate the effectiveness of classifiers for filtering spam e-mails using different matrices. Since spam is increasingly becoming difficult to detect, so these automated techniques will help in saving lot of time and resources required to handle e-mail messages.

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

Dr. Upasna Attri. 2012. \u201cComparative Study of Gaussian and Nearest Mean Classifiers for Filtering Spam E-mails\u201d. Global Journal of Computer Science and Technology - E: Network, Web & Security GJCST-E Volume 12 (GJCST Volume 12 Issue E11): .

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Issue Cover
GJCST Volume 12 Issue E11
Pg. 25- 32
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Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

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July 10, 2012

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English

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The development of data-mining applications such as classification and clustering has shown the need for machine learning algorithms to be applied to large scale data. The article gives an overview of some of the most popular machine learning methods (Gaussian and Nearest Mean) and of their applicability to the problem of spam e-mail filtering. The aim of this paper is to compare and investigate the effectiveness of classifiers for filtering spam e-mails using different matrices. Since spam is increasingly becoming difficult to detect, so these automated techniques will help in saving lot of time and resources required to handle e-mail messages.

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Comparative Study of Gaussian and Nearest Mean Classifiers for Filtering Spam E-mails

Dr. Upasna Attri
Dr. Upasna Attri Punjab Technical University, Jalandhar (India)
Harpreet Kaur
Harpreet Kaur

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