The Real Estate Price Analysis And Prediction Research Based On Data Mining

With the continuous development of the social market economy, the real estateindustry has become an important pillar industry of the national economy, the rise andfall of the real estate industry directly affects the individual, the collective thatnational interests. Therefore, to ensure the healthy development of the real estateindustry is a very important task. So how to ensure the healthy development of thereal estate industry do? In addition to the necessary national policies and measures todeal with real estate prices are also reasonable prediction and analysis, one can locatethe relevant departments of the government land auction prices; secondly also helpreal estate developers budget of profit gains; finally also help buyers assess thenormal real estate prices.In recent years, data mining technology continues to develop and penetrate thereal estate industry. Due to the constant increase in all types of data over time, thusconstituting a real estate data sea. If only to make predictions on real estate pricesthrough observation or inductive method, it will be a very big task workload. Datamining technology is precisely the dig but useful for our decision-making process ofknowledge and information from a large number of unknown information. This willpredict real estate prices provide a strong technical support.In this paper, mining data from existing real estate transaction obtainedassociation rules, and from analysis, a more accurate model. The first is associatedwith the use of real estate properties associated SQL2005analysis, factors associatedwith a relatively high degree from a number of factors that affect real estate prices asa parameter. Secondly, combined with the practical examples of the model chosen inthis article were verified.