融合模拟退火的随机森林房价评估算法.

The traditional housing prices evaluation which is using random forest algorithm has a large number of parameter selection problems and the parameters has great influence on the accuracy of the algorithm. In order to solve the above problem, this paper proposed a new algorithm combined the random forest algorithm and simulated annealing algorithm about the housing prices evaluation. Firstly, this paper tested the sensitivity of parameters by 10 times 10-cross-validation method and selected the parameters which were sensitive of the random forest algorithm. Secondly, it used the simulat ed annealing algorithm to optimize the sensitive parameters iteratively. Through comparing t o the grid searc h algorithm and ra ndom search algorithm, it found the simulated annealing algorithm was better in th e running time a nd algorithm accuracy, whic h made up the d efects of th e time-consuming and the l ow-accuracy of the random search algorithm in the grid searc h when sel e cting para met e rs. At l ast, this paper applied th e random forest algorithm combing with simulated annealing to the housing prices evaluation, and formed a new evalu-ation algorithm. Compared with the traditional random forest price estimation algorithms, the results show that the proposed al-gorithm reduces the error value, inc reases the goodness of fit value, a nd improves markedly the accuracy of the evaluation. [ABSTRACT FROM AUTHOR]