A House Price Prediction Model Based on Deep Belief Network
Lü Hao;Tianjin Nankai Construction Investment Company;
Deep belief network was used in the prediction of house prices. A deep learning prediction model which can assist housing price research was established. The price data of 1 461 houses that have been traded in the Ames housing market published by the Kaggle contest platform were analyzed. Partial least squares,artificial neural network and support vector machine were used as comparative experiments to verify the accuracy of the proposed model. The experimental results show that the proposed model can achieve good results in housing price prediction.
【CateGory Index】： F299.23