An ensemble based approach using a combination of clustering and classification algorithms to enhance customer churn prediction in telecom industry.
Syed Fakhar BilalAbdulwahab Ali AlmazroiSaba BashirFarhan Hassan KhanAbdulaleem Ali AlmazroiPublished in: PeerJ Comput. Sci. (2022)
Keyphrases
- learning algorithm
- customer churn
- churn prediction
- ensemble classifier
- classification algorithm
- prediction accuracy
- decision trees
- data clustering
- benchmark datasets
- unsupervised learning
- ensemble methods
- neural network
- machine learning
- clustering algorithm
- classification accuracy
- feature selection
- prediction model
- support vector
- decision rules
- training set
- feature space
- machine learning methods
- random forest
- clustering analysis
- social network analysis
- clustering method
- cluster analysis
- case study
- feature vectors
- feature set
- data warehouse
- k means
- real world