Abstract
User behavior contains a large amount of value information, and assessing user behavior can be a good guide for enterprises to develop service policies. The current power user behavior assessment model mainly relies on the past evaluation theories, and the selected indicators are not comprehensive enough, leading to unsatisfactory evaluation results. In order to optimize the above problems, the construction of the power user behavior assessment model based on 95598 user portraits will be studied. After text conversion, data cleaning and variable attribute analysis of 95598 grid customer service phone data, 95598 user portrait is established. The logistic regression model is combined with decision tree algorithm to complete the construction of the electric power user behavior evaluation model. The results of the model feasibility study show that the correct rate of the constructed electric power user behavior assessment model is higher than 95%, and the model has a high accuracy of predicting the abnormal behavior of electric power users, which has good practical application effect.
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