Examination of the Factors Affecting Household Rental Housing Demand Through Data Mining

Houses are an irreplaceable tool for the need for shelter However, as a result of the global economic, cultural and technological changes encountered in recent years they have become a source of assurance for the future and one of the most significant indicators of life-style and wealth and social prestige as well as meeting the basic need for shelter. This causes house to become a heterogeneous good and to involve many characteristics. The effectiveness level of different characteristics of the house on the market value of the house is predicted using hedonic pricing model based on micro-economic theory. The aim of the study is to analyze the factors affecting rental housing demand of households through data mining methods. 2341 household data has been referenced and 49 data title was selected as the basis ofthe study in which Household Budget Survey data of 2015 has been used. As a result of the study, it has been determined that Decision Tree algorithm which is one of the Data Mining methods yielded the best result