Statistical analysis for predicting residents' travel mode based on random forest


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Random forest has achieved good results in the prediction task, but due to the complexity of travel mode and the uncertainty of random forest, the prediction accuracy of travel mode is low. To improve the accuracy of prediction, this paper proposes a residents' travel modes prediction method based on the random forest. To extract valuable feature information, the questionnaire survey data is collected, which is pre-processed by three kinds of appropriate methods. Then, each feature is analysed by the statistical learning method to obtain the important feature of transportation selection. Finally, a random forest is constructed to predict the travel mode of residents' selection of transportation. The parameters of random forest are modified and improved to achieve higher prediction accuracy of travel mode. The experimental results show that the method proposed in this paper effectively improves the prediction accuracy of the travel mode.
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Key words
residents' travel mode,statistical analysis,random forest
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