摘要
随着社会的进步与发展,我国机动车的保有量逐步上升,与此同时,车辆的交易市场也在逐步扩大。因此,合理对车辆价格进行评估成为车辆交易市场最值得关注的事情。文章通过对不同车型的几类特征使用热力图进行相关性分析并且删除冗余特征,最后用四种机器学习模型对数据进行预测,通过一系列量化指标得出预测效果最好的模型。实验结果表明,该模型具有较高的精确度,能够有效预测车辆价格,同时也能为二手车交易市场提供一定参考。
With the progress and development of society,the number of motor vehicles in China is gradually rising,and at the same time,the vehicle trading market is also gradually expanding.Therefore,a reasonable evaluation of the vehicle price has become the most noteworthy thing in the vehicle trading market.In this paper,several types of features of different vehicles are analyzed using thermal maps for correlation and redundant features are deleted.Finally,four machine learning models are used to predict the data,and the model with the best prediction effect is obtained through a series of quantitative indicators.The experimental results show that the model has a high accuracy and can effectively predict the vehicle price,and also provide some reference for the second-hand car market.
作者
李博涵
LI Bo-han(School of Electromechanical and Vehicle Engineering,Chongqing Jiaotong University,Chongqing 400074,China)
出处
《价值工程》
2023年第1期107-110,共4页
Value Engineering
关键词
车辆价格
相关性分析
机器学习
car price
correlation analysis
machine learning
