摘要
由一名新闻记者-机器人与机器学习每日新闻的工作人员新闻编辑-调查人员发布了关于人工智能的新报告。根据NewsRx记者从中华人民共和国北京的新闻报道，研究表明，"本研究深入探讨了预测房价的意义和方法"。本报记者引用北京交通大学的一篇研究报告：“利用Kaggle的数据，选取了与房价相关程度较高的10个变量，包括总体、GrLivArea和GarageCa RS，并利用随机森林和多元线性回归等模型进行预测和比较，结果表明，对于线性关系较强的数据，多元线性回归模型的预测性能优于随机森林模型。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Investigators publish new report on artificial in telligence. According to news reporting from Beijing, People’s Republic of China , by NewsRx journalists, research stated, “This study delves into the significan ce and methods of predicting housing prices.” Our news reporters obtained a quote from the research from Beijing Jiaotong Univ ersity: “Utilizing a dataset from Kaggle, the author selected 10 variables highl y correlated with housing prices, including OverallQual, GrLivArea, and GarageCa rs. Various models such as random forest and multiple linear regression were emp loyed for prediction and comparison. Results indicate that for data with strong linear relationships, the predictive performance of the multiple linear regressi on model surpasses that of the random forest model.”
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