Application of SVM Based on Rough Set in Real Estate Investment Environment Comprehensive Evaluation

Ting Wang, Yanqing Li
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Abstract

The stable prices rose in the real estate market attracted a large amount of funds injected into it, to choose a good investment environment has been a keyto get profit from investment. In this paper, a Support Vector Machine (SVM) model is founded to do the evaluation. Based on the comprehensive evaluation index system of real estate investment environment, Rough set (RS) is introduced to reduce numbers of evaluation indicators, thus reducing the dimensions of the input space of SVM., when treating the reduced data as the input space of SVM, we find that both the convergence speed and the classify accuracy are enhanced in comparison with the general SVM comprehensive evaluation method and BP evaluation method.
基于粗糙集的SVM在房地产投资环境综合评价中的应用
房地产市场价格的稳定上涨吸引了大量的资金注入其中,选择一个良好的投资环境已经成为投资获利的关键。本文建立了支持向量机(SVM)模型进行评价。在房地产投资环境综合评价指标体系的基础上,引入粗糙集(RS)来减少评价指标的数量,从而降低支持向量机输入空间的维数。将约简后的数据作为支持向量机的输入空间,与一般的支持向量机综合评价方法和BP评价方法相比,其收敛速度和分类精度都有提高。
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