Dynamic estimation model of insurance product recommendation based on Naive Bayesian model
Bo Zhang, Dehua Kong · 2020
Aiming at the dynamic estimation of insurance product recommendation, considering the particularity and complexity of purchasing insurance product and the uncertainty of influencing factors, a dynamic estimation model of insurance product recommendation based on Naive Bayes is proposed. The model combines customer insurance information with machine learning. The results show that the naive Bayesian classification algorithm can be compared with the decision tree and neural network classification algorithm, showing high accuracy and high speed.