Customer churn modeling in telecommunication using a novel multi-objective evolutionary clustering-based ensemble learning

Open Access

Peer-reviewed

Research Article

About the Authors

Kaveh Faraji Googerdchi

Contributed equally to this work with: Kaveh Faraji Googerdchi, Shahrokh Asadi, Seyed Mohammadbagher Jafari

Roles Data curation, Writing – original draft

Affiliation Faculty of Management and Accounting, College of Farabi, University of Tehran, Tehran, Iran

Shahrokh Asadi

Contributed equally to this work with: Kaveh Faraji Googerdchi, Shahrokh Asadi, Seyed Mohammadbagher Jafari

Roles Supervision

Affiliation Faculty of Engineering, College of Farabi, University of Tehran, Tehran, Iran

Seyed Mohammadbagher Jafari

Contributed equally to this work with: Kaveh Faraji Googerdchi, Shahrokh Asadi, Seyed Mohammadbagher Jafari

Roles Writing – review & editing

Affiliation Faculty of Management and Accounting, College of Farabi, University of Tehran, Tehran, Iran

The authors have declared that no competing interests exist.

Machine learning
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Algorithms
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Optimization
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Evolutionary algorithms
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Artificial neural networks
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Decision tree learning
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Telecommunications
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Memory recall
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