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Exploring nested ensemble learners using overproduction and choose approach for churn prediction in telecom industry.
Mahreen Ahmed
Hammad Afzal
Imran Siddiqi
Muhammad Faisal Amjad
Khawar Khurshid
Published in:
Neural Comput. Appl. (2020)
Keyphrases
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churn prediction
random forest
genetic k means algorithm
telecommunication services
customer churn
rule induction
ensemble methods
credit risk
data mining
decision trees
neural network
base classifiers
feature set
multi label
genetic programming
rough sets
support vector