Multi-class Churn Classification

Multi-Class Churn Classification is a predictive modeling task in customer churn analysis that categorizes customers into more than two discrete outcome classes—such as non-churn, voluntary churn, and involuntary churn—thereby extending binary churn prediction to capture multiple distinct behavioral trajectories.

5

Publications

194

Citations

16

Authors

7

Institutions

Publications per year

2017–2026

4

Authors

16

  1. BB
    Belaid Bouikhalene

    Université Sultan Moulay Slimane, Morocco

    1 publications · 19 citations

    1

    h-index

  2. SA
    Sajid Anwar

    Institute of Management Sciences Peshawar, Pakistan

    1 publications · 15 citations

    1

    h-index

  3. AD
    Ait Daoud Rachid

    Université Sultan Moulay Slimane, Morocco

    1 publications · 19 citations

    1

    h-index

  4. MK
    Mai Kiguchi

    University of Agder, Norway

    1 publications · 57 citations

    1

    h-index

  5. GG
    Gaurav Gupta

    Punjabi University, India

    1 publications · 35 citations

    1

    h-index

1–5 of 16

Venues

  1. Applied Soft Computing

    1 publications · 57 citations

    1

    h-index

  2. Microprocessors and Microsystems

    MICPRO · 1 publications · 35 citations

    1

    h-index

  3. International Journal of Data Science and Analytics

    JDSA · 1 publications · 68 citations

    1

    h-index

  4. 1

    h-index

  5. Computational Economics

    1 publications · 14 citations

1–5