Journal ArticleDOI
Customer churn prediction in the telecommunication sector using a rough set approach
TLDR
This study proposes an intelligent rule-based decision-making technique, based on rough set theory (RST), to extract important decision rules related to customer churn and non-churn, and shows that RST based on GA is the most efficient technique for extracting implicit knowledge in the form of decision rules from the publicly available, benchmark telecom dataset.About:
This article is published in Neurocomputing.The article was published on 2017-05-10. It has received 155 citations till now. The article focuses on the topics: Customer retention & Decision rule.read more
Citations
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Journal ArticleDOI
A Churn Prediction Model Using Random Forest: Analysis of Machine Learning Techniques for Churn Prediction and Factor Identification in Telecom Sector
TL;DR: The results reveal that the proposed churn prediction model produced better churn classification using the RF algorithm and customer profiling using k-means clustering, and provides factors behind the churning of churn customers through the rules generated by using the attribute-selected classifier algorithm.
Journal ArticleDOI
Customer churn prediction in telecommunication industry using data certainty
TL;DR: A novel CCP approach is presented based on the above concept of classifier's certainty estimation using distance factor, which shows that the distance factor is strongly co-related with the certainty of the classifier.
Journal ArticleDOI
Machine-Learning Techniques for Customer Retention: A Comparative Study
TL;DR: Results show that both random forest and ADA boost outperform all other techniques with almost the same accuracy 96%, and both Multi-layer perceptron and Support vector machine can be recommended as well with 94% accuracy.
Journal ArticleDOI
Integrating principle component analysis and weighted support vector machine for stock trading signals prediction
Yingjun Chen,Yijie Hao +1 more
TL;DR: A complete and efficient method which integrates principal component analysis ( PCA) into weighted support vector machine (WSVM) to forecast trading points of the stock (PCA- WSVM) is proposed and can be applied to forecast the stock trading signals in the real-world application.
Journal ArticleDOI
An Empirical Study on Customer Segmentation by Purchase Behaviors Using a RFM Model and K-Means Algorithm
TL;DR: The effectiveness of the method proposed in this paper is supported by improvement results of some key performance indices such as the growth of active customers, total purchase volume, and the total consumption amount.
References
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Journal ArticleDOI
Rough sets
TL;DR: This approach seems to be of fundamental importance to artificial intelligence (AI) and cognitive sciences, especially in the areas of machine learning, knowledge acquisition, decision analysis, knowledge discovery from databases, expert systems, decision support systems, inductive reasoning, and pattern recognition.
Journal ArticleDOI
Customer switching behavior in service industries: An exploratory study
TL;DR: In this paper, customer switching behavior damages market share and profitability of service firms yet has remained virtually unexplored in the marketing literature, and the author reports results of a critical incid...
Proceedings ArticleDOI
Group formation in large social networks: membership, growth, and evolution
TL;DR: It is found that the propensity of individuals to join communities, and of communities to grow rapidly, depends in subtle ways on the underlying network structure, and decision-tree techniques are used to identify the most significant structural determinants of these properties.
Proceedings ArticleDOI
WEKA: a machine learning workbench
TL;DR: WEKA is a workbench for machine learning that is intended to aid in the application of machine learning techniques to a variety of real-world problems, in particular, those arising from agricultural and horticultural domains.