摘要
随着居民可支配收入的增加与我国汽车保有量的提升,二手车交易量也不断提高。但是,随着二手车线上交易的逐步发展,也暴露了一些问题,二手车成交过程中的价格量化问题,定价过于随性不够公开透明。因此,本文从解决实际问题出发,构建一个基于XGBoost算法的价格预测模型,使用从各二手车平台爬虫的数据作为数据集,通过对不同车辆情况属性的训练,对其最终成交价格进行预估,以用于解决实际生活中对二手车成交价格量化困难,具有重要的研究意义和实用价值。
With the increase of residents’disposable income and the increase of China’s car ownership,second-hand car trading volume is also increasing.However,with the gradual development of second-hand car online trading,there are also exposed some problems.The price quantification problem in the process of second-hand car transaction is too casual and not open and transparent enough Therefore,this article embarks from the solution actual problem,build a price forecasting model based on XGBoost algorithm,using the data as a data set from the used car platform crawler,through the training,the attributes of different vehicle condition to estimate of the final sale price,clinch a deal on a used car to solve real life price quantitative difficulties,has important research significance and real With the value.
作者
李原吉
李丹
唐淇
Li Yuanji;Li Dan;Tang Qi(Jincheng College,Sichuan University,Chengdu Sichuan,611731)
出处
《电子测试》
2021年第21期47-49,共3页
Electronic Test
