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http://dx.doi.org/10.14400/JDC.2018.16.12.217

Development of Forecasting Model for the Initial Sale of Apartment Using Data Mining: The Case of Unsold Apartment Complex in Wirye New Town  

Kim, Ji Young (Hanam Urban Innovation Corporation)
Lee, Sang-Kyeong (Dept. of Urban Planning, Gachon University)
Publication Information
Journal of Digital Convergence / v.16, no.12, 2018 , pp. 217-229 More about this Journal
Abstract
This paper aims at applying the data mining such as decision tree, neural network, and logistic regression to an unsold apartment complex in Wirye new town and developing the model forecasting the result of initial sale contract by house unit. Raw data are divided into training data and test data. The order of predictability in training data is neural network, decision tree, and logistic regression. On the contrary, the results of test data show that logistic regression is the best model. This means that logistic regression has more data adaptability than neural network which is developed as the model optimized for training data. Determinants of initial sale are the location of floor, direction, the location of unit, the proximity of electricity and generator room, subscriber's residential region and the type of subscription. This suggests that using two models together is more effective in exploring determinants of initial sales. This paper contributes to the development of convergence field by expanding the scope of data mining.
Keywords
Unsold apartment; Initial sale; Data mining; Decision tree; Neural network; Logistic regression;
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Times Cited By KSCI : 6  (Citation Analysis)
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