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Abstract
Our lives cannot do without the internet. How to improve the network quality has always been an essential problem. The paper explores the important factors of online service satisfaction and the best predicting model. Based on the data offered by Beijing Mobile Company, we identify main factors affecting online service satisfaction by calculating their mutual information values. The factors include signal problem factors, scene factors and software usage factors. Additionally, based on decision tree model and models with decision tree as base learner, we predict the online service satisfaction. The result shows that random tree model with One Vs Rest mode has the greatest accuracy among the models which offers telecommunications companies insight.
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