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A Prudent Based Approach for Customer Churn Prediction

  • Conference paper
Beyond Databases, Architectures and Structures (BDAS 2015)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 521))

Abstract

This study contributes to formalize a three phase customer churn prediction technique. In the first phase, a supervised feature selection procedure is adopted to select the most relevant subset of features by laying-off the redundancy and increasing the relevance that leads to reduced and highly correlated features set. In the second phase, a knowledge based system (KBS) is built through Ripple Down Rule (RDR) learner which acquires knowledge about seen customer churn behavior and handles the problem of brittle in churn KBS through prudence analysis that will issue a prompt to the decision maker whenever a case is beyond the maintained knowledge in the knowledge database. In the final phase, a technique for Simulated Expert (SE) is proposed to evaluate the Knowledge Acquisition (KA) in KB system. Moreover, by applying the proposed approach on publicly available dataset, the results show that the proposed approach can be a worthy alternate for churn prediction in telecommunication industry.

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Author information

Authors and Affiliations

  1. Institute of Management Sciences, Peshawar, Khyber Pukhtunkhwa, Pakistan

    Adnan Amin, Faisal Rahim & Sajid Anwar

  2. Saudi Electronic University, Riyadh, Saudi Arabia

    Muhammad Ramzan

Authors
  1. Adnan Amin
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  2. Faisal Rahim
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  3. Muhammad Ramzan
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  4. Sajid Anwar
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Corresponding author

Correspondence to Adnan Amin .

Editor information

Editors and Affiliations

  1. Silesian University of Technology, Gliwice, Poland

    Stanisław Kozielski

  2. Silesian University of Technology, Gliwice, Poland

    Dariusz Mrozek

  3. Silesian University of Technology, Gliwice, Poland

    Paweł Kasprowski

  4. Silesian University of Technology, Gliwice, Poland

    Bożena Małysiak-Mrozek

  5. Silesian University of Technology, Gliwice,, Poland

    Daniel Kostrzewa

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© 2015 Springer International Publishing Switzerland

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Amin, A., Rahim, F., Ramzan, M., Anwar, S. (2015). A Prudent Based Approach for Customer Churn Prediction. In: Kozielski, S., Mrozek, D., Kasprowski, P., Małysiak-Mrozek, B., Kostrzewa, D. (eds) Beyond Databases, Architectures and Structures. BDAS 2015. Communications in Computer and Information Science, vol 521. Springer, Cham. https://doi.org/10.1007/978-3-319-18422-7_29

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  • DOI: https://doi.org/10.1007/978-3-319-18422-7_29

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-18421-0

  • Online ISBN: 978-3-319-18422-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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