In this paper, AdaBoost algorithm, a popular and effective prediction method, is applied to predict the prediction of claim frequency of auto insurance, which plays an important part of property insurance companies. Using a real dataset of car insurance, we reduce the frequency prediction problem to be a multi-class problem, in turn we employ the mixed method called multi-class AdaBoost tree (a combination of decision tree with adaptive boosting) as our predictor. | Using multi-class adaboost tree for prediction frequency of auto insurance
