The Review of Attributes Influencing Housing Prices using Data Mining Methods
Keywords:
Data mining, CRISP-DM, CART algorithm, C5 algorithm, Neural networks model.Abstract
Prices of housing show an alteration throughout the world. The reason of this is characteristics of housing such as age, tax, number of rooms, per capita crime rate by town and so on. In this study, we carry out the stages of the CRISP-DM process to investigate attributes influencing prices of housing. We use CART, C5 decision tree algorithms and Neural networks model in modeling phase. Also, we use cross-validation method in modeling evaluation phase. It is shown that C5 model is the most appropriate model with the highest validation rate.
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