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Training Logistic Regression Model by Hybridized Multi-verse Optimizer for Spam Email Classification

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Proceedings of International Conference on Data Science and Applications

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 552))

Abstract

Spam emails pose a significant threat to end users, annoying them and wasting their time. To counter this problem, numerous spam detection systems have been proposed recently, where the most of the solutions have grounds in the machine learning algorithms, due to their efficiency in classification tasks. Unfortunately, existing spam detection solutions typically face low detection rate and generally have troubles in dealing with high-dimensional data. To address this problem, this paper suggests a hybrid spam detection approach by combining the logistic regression classifying model with the hybridized multi-verse optimizer swarm intelligence metaheuristics. The proposed approach was validated on a public benchmark dataset (CSDMC2010) and compared to other cutting-edge techniques. The obtained results indicate that the suggested hybrid approach outperforms other spam detection solutions included in the comparative analysis, by achieving the highest classification accuracy.

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Acknowledgements

The paper is supported by the Ministry of Education, Science and Technological Development of Republic of Serbia, Grant No. III-44006.

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Authors and Affiliations

  1. Singidunum University, Danijelova 32, 11000, Belgrade, Serbia

    Miodrag Zivkovic, Aleksandar Petrovic, Nebojsa Bacanin, Marko Djuric, Ana Vesic, Ivana Strumberger & Marina Marjanovic

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  1. Miodrag Zivkovic
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  2. Aleksandar Petrovic
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  3. Nebojsa Bacanin
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  4. Marko Djuric
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  5. Ana Vesic
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  6. Ivana Strumberger
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  7. Marina Marjanovic
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Corresponding author

Correspondence to Miodrag Zivkovic .

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Editors and Affiliations

  1. Department of Computer Science and Engineering and Information Technology, Jaypee Institute of Information Technology, Noida, India

    Mukesh Saraswat

  2. Department of Computer Science and Engineering, Jadavpur University, Kolkata, India

    Chandreyee Chowdhury

  3. Department of Computer Science and Engineering, Jadavpur University, Kolkata, India

    Chintan Kumar Mandal

  4. Data Science Institute, University of Technology Sydney, Sydney, NSW, Australia

    Amir H. Gandomi

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Zivkovic, M. et al. (2023). Training Logistic Regression Model by Hybridized Multi-verse Optimizer for Spam Email Classification. In: Saraswat, M., Chowdhury, C., Kumar Mandal, C., Gandomi, A.H. (eds) Proceedings of International Conference on Data Science and Applications. Lecture Notes in Networks and Systems, vol 552. Springer, Singapore. https://doi.org/10.1007/978-981-19-6634-7_35

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