| 基于支持向量机的上海市宝山区房价的判别与预测 |
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| 引用本文： | 李志峰,李金伟,吉伟. 基于支持向量机的上海市宝山区房价的判别与预测[J]. 湖北师范学院学报(自然科学版), 2011, 31(4): 60-65 |
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| 作者姓名： | 李志峰 李金伟 吉伟 |
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| 作者单位： | 湖北师范学院数学与统计学院;上海科东房地产土地估价有限公司 |
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| 摘 要： | 房价问题是关系民生的热点话题,统计分析房价的影响因素时,收集的基本上是小样本、多变量的数据。先用多元统计方法将宝山区12城镇(街道)的房价进行分类和回归分析,然后运用支持向量机(Sup-port Vector Machines,SVM)建立了判别和预测模型,对城镇房价进行分类判别和预测比较,结果说明支持向量机对于小样本的研究有一定的优势。
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| 关 键 词： | 支持向量机 判别分析 预测 |
Discriminant analysis and prediction of house prices based on support vector machines |
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| LI Zhi-feng,LI Jin-wei,JI Wei. Discriminant analysis and prediction of house prices based on support vector machines[J]. Journal of Hubei Normal University(Natural Science), 2011, 31(4): 60-65 |
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| Authors: | LI Zhi-feng LI Jin-wei JI Wei |
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| Affiliation: | 1.College of Mathematics and Statistics,Hubei Normal University,Huangshi 435002,China; 2.Shanghai Kedong Real Estate Appraisal Co.,Itd,Shangshi 200032,China) |
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| Abstract: | The problem of house prices is the hot topics about people＇s livelihood, when we analyze the influence factors of house prices in statistical methods , the collected data are basically small sample and multivariate . In this paper , we firstly classify twelve towns （streets） in Shanghai Baoshan District andmake two kinds of regression analysis in multivariate statisti- cal analysis ,then establish models to cluster, discriminant ,predict and compare the house prices by Support Vector Machines （ SVM）, the result shows that SVM has certain advantages for the research of small sample. |
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| Keywords: | support vector machine discriminant analysis prediction |
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