Predicting preferences of university students for prepaid vs post paid cell phone service plans

作者:

Highlights:

摘要

Information and communication technologies have recently become widely used, especially among the younger population. In this study, the factors affecting the preference of undergraduate students for prepaid or postpaid cell phone service plans were analyzed and a multi-layer perceptron type feed forward neural network model was developed to predict the preferences. Using the responses to the questionnaire administered to a group of undergraduate students in Istanbul University, the factors determining the preference for service plan were determined with χ2 test for independence. A classification model based on multi-layer perceptron type neural networks was developed. The classification accuracy of this model was compared to linear regression, LDA, QDA, Naive Bayes and decision tree approaches and shown to be superior.

论文关键词:Classification,Neural networks,LDA,QDA,Naive Bayes,Decision tree,Cell phone service

论文评审过程:Available online 26 January 2011.

论文官网地址:https://doi.org/10.1016/j.eswa.2011.01.122