MapReduce mRMR: Random Forests-Based Email Spam Classification in Distributed Environment-Reference-Cited by-同舟云学术

MapReduce mRMR: Random Forests-Based Email Spam Classification in Distributed Environment

Published:2019-10-25 Issue: Volume: Page:241-253
ISSN:2194-5357
Container-title:Data Management, Analytics and Innovation
language:
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Author:

Sri Vinitha V.,Karthika Renuka D.

Publisher

Springer Singapore

Link

http://link.springer.com/content/pdf/10.1007/978-981-32-9949-8_18

Reference13 articles.

1. Zhang, Y., He, J., Xu, J.: A new anti-spam model based on e-mail address concealment technique. J. Nat. Sci. 23(1), 79–83 (2018)

2. Khalaf, O.I., Abdulsahib, G.M., Salman, A.D.: Handling dimensionality reduction in spam e-mail classification. J. Adv. Res. Dyn. Control Syst. 10(1), 691–697 (2018)

3. Bassiouni, M., Ali, M., El-Dahshan, E.A.: Ham and spam e-mails classification using machine learning techniques. J. Appl. Secur. Res. 13(3), 315–331 (2018)

4. Kaur, J., Priyanka: Feature selection based efficient machine learning technique for email spam predicition. Int. J. Eng. Appl. Sci. Technol. 2(12), 13–19 (2018)

5. Vijayasekaran, G., Rosi, S.: Spam and email detection in big data platform using naives bayesian classifier. Int. J. Comput. Sci. Mob. Comput. (IJCSMC) 7(4), 53–58 (2018)

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