Abstract
According to hedonic price theory, using classification algorithm of the machine learning which include SVM, Naive Bayesian and KNN, establish the internal mapping relationship between feature variables that include prices of housing and air quality. Air quality in urban residential district is predicted by feature variables. Finally, experiments have conducted on the data set of residential district In Tianhe, Guangzhou city, showed that the most accuracy. The method is very practical and stable for air quality in urban residential district prediction. The new method has a strong practical value as reference methods for buyers.
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