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International Conference on Computational Collective Intelligence

ICCCI 2018: Computational Collective Intelligence pp 335–344Cite as

Ant Colony Optimization Algorithms in the Problem of Predicting the Efficiency of the Bank Telemarketing Campaign

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11056))

Abstract

In this article, we analyze the effectiveness of the telemarketing campaign developed by the Portuguese bank. The main goal of this analysis was to estimate, is there existing ant colony algorithms are capable of building classifiers that lead to increasing the effectiveness of the telemarketing campaign. An additional question was related to the problem of adjusting the whole campaign to the actual needs of clients. Presented data include 17 attributes, including information about the efficiency of carried out conversations related to the bank deposit offer. The analysis presented in this article was developed on the basis of algorithms used for the decision trees construction such as CART and C4.5. As a result, a prediction allowing to estimate the result of the telemarketing conversation with a client was made. Conducted experiments allowed for the comparison of different classifiers. The comparison was made on the basis of different measures of classification efficiency. It is especially important in the case of the real-world data, where cardinality of decision classes is uneven. Conducted experiments allowed for the comparison of different classifiers. Initial evaluation confirms, that such an approach could be efficiently used for the dynamic data sets, like streams.

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Acknowledgement

This paper is co-funded by the National Science Centre, Poland: 2017/01/X/ST6/01477.

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Authors and Affiliations

  1. Faculty of Informatics and Communication, Department of Knowledge Engineering, University of Economics, 1 Maja 50, 40-287, Katowice, Poland

    Jan Kozak & Przemysław Juszczuk

Authors
  1. Jan Kozak
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  2. Przemysław Juszczuk
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Corresponding author

Correspondence to Jan Kozak .

Editor information

Editors and Affiliations

  1. Faculty of Information Technology, Ton Duc Thang University, Ho Chi Minh City, Vietnam

    Ngoc Thanh Nguyen

  2. Department of Computer Science and Creative Technologies, University of the West of England, Bristol, United Kingdom

    Elias Pimenidis

  3. Department of Computer Science and Creative Technologies, University of the West of England, Bristol, United Kingdom

    Zaheer Khan

  4. Faculty of Computer Science and Management, Wrocław University of Science and Technology, Wrocław, Poland

    Bogdan Trawiński

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Kozak, J., Juszczuk, P. (2018). Ant Colony Optimization Algorithms in the Problem of Predicting the Efficiency of the Bank Telemarketing Campaign. In: Nguyen, N., Pimenidis, E., Khan, Z., Trawiński, B. (eds) Computational Collective Intelligence. ICCCI 2018. Lecture Notes in Computer Science(), vol 11056. Springer, Cham. https://doi.org/10.1007/978-3-319-98446-9_31

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  • DOI: https://doi.org/10.1007/978-3-319-98446-9_31

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-98445-2

  • Online ISBN: 978-3-319-98446-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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