Study on the Classifier for Mobile Phone Users Considering the Classification Cost——Based on the Perspective of Data Balance

Abstract

Abstract: Traditional classification algorithms cannot effectively improve the classification effect of users when dealing with unbalanced data. Based on the user information data from a branch of China Mobile Communications Corporation, this study makes, from the data balance perspective, an empirical analysis on mobile phone classifier, the optimal threshold, expected risk, and the relationship between the classification of the cost. Research findings:the accuracy of mobile phone exchange is higher than that of the original data set; With the increase of the threshold value of the classifier, same classification cost ratio, the expected risk appears to increase first and then decrease; the classification result of whether the user changes the mobile phone or not is influenced by the balance of data and the set of classification cost ratio. These conclusions can provide a decision-making basis for mobile phone sellers and manufacturers to improve their management methods.

Key words: non-equilibrium data, classifier, classification accuracy, classification cost

Wang Chaofa, Wang Shubin, Wang Chengjun. Study on the Classifier for Mobile Phone Users Considering the Classification Cost——Based on the Perspective of Data Balance[J]. Management Review, 2021, 33(9): 177-186.

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