Research On Real Estate Batch Appraisal Method Under Data Drive

The real estate industry is one of the most important industries driving economic development in my country.With the rapid expansion of urban area,the supply of land in the city center is becoming more and more scarce.The real estate transaction market has changed from a new housing transaction market to a second-hand housing transaction market.Real estate appraisal plays a very important role in guiding people to buy and sell real estate,the government formulating taxation and formulating economic development strategies.Under this circumstance,the government,intermediaries,and buyers and sellers have more and more urgent needs for perfect second-hand housing market information and accurate second-hand housing prices.With the development of computer technology and information technology in the 21st century,people are no longer limited to traditional manual evaluation methods in real estate evaluation.Scientific researchers are constantly exploring new methods to solve the need to manually complete a large amount of data processing and calculation in the process of batch evaluation.The update of computer technology has gradually brought the method of big data real estate evaluation into people’s field of vision.In the research of real estate evaluation methods,with the advancement of big data technology and artificial intelligence,the use of big data technology to conduct real estate evaluation has gradually become a new research focus,and its application in the field of real estate evaluation has gradually become hot and has gained more much market recognition.This study obtained nearly 6000 second-hand housing listing information in Dalian from online public data as the original data,and used the latest machine learning algorithm combined with real estate evaluation theory to explore the feasibility of data-driven real estate evaluation.The comparison finally came to the conclusion that compared with the traditional machine learning method,the CatBoost algorithm has the best performance in the research on real estate price evaluation.Compared with other algorithms,it has higher accuracy and efficiency of real estate batch evaluation.The CatBoost algorithm is adopted The real estate batch evaluation has a high accuracy rate and high social application value,which provides a new reference for the real estate batch evaluation technology.Through machine learning modeling and evaluation,the contradiction between big data evaluation theory and practical application is eliminated,the real estate case data is fully utilized,batch evaluation is the main evaluation object,and real estate evaluation theory and technology are updated,so that traditional theoretical methods and modern technology are closely connected,to realize the two-way drive appraisal process of real estate appraisal.