Predicted the Used Sailboat Price by Decision Tree and Multiple Regression Model

Abstract

In this paper, three mathematical models are established to explore the factors that influence the price of used sailboat, and predicts the price of used sailboat in different regions. First, clean and process the dataset, and the node centrality analysis is carried out. Next, a decision tree model is used to explain the price of the sailboat. In order to predict the price of sailing ships in different regions, this paper transforms geographical region variables into dummy variables, and uses multiple linear regression method to evaluate the influence of geographical region on the price. Then, an ANOVA model is established to analyze the price and regional impact of different types of sailboats. Finally, a cluster analysis algorithm is established to classify used sailboat by various classification factors.