Application Of Multiple Regression Algorithm to Price Prediction Model: Taking Sailboat Price as An Example

Abstract

The sailboat market is becoming more and more mature, but market price prediction is rarely studied. Therefore, on the basis of considering the characteristics of sailboats themselves, this paper also considers the influence of regional effects on sailboat prices from three aspects: taxation, interest rate and economic conditions. Multiple linear regression model was used to fit the data, and the weight size of each index was analyzed to study the impact of each index on sailboat price. The results show that: (1) the MAE of the monolithic sailboats in the test set is 8478.0. However, the MAE of catamaran is 10,868.4. The fitting results are good, indicating that the multiple linear regression model is suitable for predicting sailboat prices. (2) The weight of the two indicators, tax change rate and GDP per capita, is higher in monolithic sailboats. The weight of the expected growth rate is high but negative, indicating that monolithic sailboats are greatly affected by regional economic factors. (3) Among catamarans, only the GDP per capita is larger than that of monolithic sailboats. The effect of the rate of tax change on catamaran prices is almost negligible. The expected growth rate, although negative, is much smaller than monolithic sailboats. (4) The monolithic sailboats is much more affected by region than the catamaran. The results can provide guidance for the simulation and prediction of sailboat market prices.