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Research on Mobile Caravan Insurance Recommendation Method Based on Machine Learning

With the continuous progress of computer computing performance, network transmission and other information technology, machine learning methods are more widely used in various industries. In this paper, we study the caravan insurance recommendation algorithm based on machine learning methods for the insurance product recommendation business problem. The article analyses data exploration, data pre-processing, building classification models and balancing data sets, focusing on the taking, distribution and visualisation of the various types of feature fields of the data to show the distribution of variables. Based on the construction of a preliminary logistic regression model, this paper performs a balancing dataset operation to address the problem of dataset imbalance. The results of the model tests show that: user characteristics social class and rental house characteristics have a significant negative effect on the purchase of mobile caravan insurance; private insurance, public equipment and the number of fire insurance policies taken out have a significant positive effect on the purchase of mobile caravan insurance.