数据挖掘在房地产价格预测中的应用研究

通过基于数据挖掘理论的粗糙集和神经网络的研究,用属性约简算法约简并提取了影响房地产价格的主要指标因素,对降维后的数据进行网络学习和训练,最后用训练好的的网络检验测试样本.方法使学习训练的速度和识别率提高了,为房地产价格预测提供了一种更为有效和实用的新途径.

Application on Real Estate Price Prediction Based on a Method of Data Mining

To research the price prediction of real estate,this paper constructs a BP neural network model based on rough set.Attribute reduction is firstly used to obtain the mainly components of the factors of the real estate price to reduce the number of dimensionalities of the decision talbe.After the dimensionality reduction process,we put the new data into BP neural network to train it.Stumilation results show that,compared with the BP neural network nodel,BP neural network model based on rough set gets a higher rate on speed and recognition when trained under the worked data.The results indicate that BP neural network model based on rough set should be a better way to the price prediction of real estate.