Apartment Price Prediction Using Deep Learning and Machine Learning


KIPS Transactions on Software and Data Engineering, Vol. 12, No. 2, pp. 59-76, Feb. 2023
https://doi.org/10.3745/KTSDE.2023.12.2.59,   PDF Download:
Keywords: Real Estate, Regression, DNN, XGBoost, CatBoost, map visualization
Abstract

Since the COVID-19 era, the rise in apartment prices has been unconventional. In this uncertain real estate market, price prediction research is very important. In this paper, a model is created to predict the actual transaction price of future apartments after building a vast data set of 870,000 from 2015 to 2020 through data collection and crawling on various real estate sites and collecting as many variables as possible. This study first solved the multicollinearity problem by removing and combining variables. After that, a total of five variable selection algorithms were used to extract meaningful independent variables, such as Forward Selection, Backward Elimination, Stepwise Selection, L1 Regulation, and Principal Component Analysis(PCA). In addition, a total of four machine learning and deep learning algorithms were used for deep neural network(DNN), XGBoost, CatBoost, and Linear Regression to learn the model after hyperparameter optimization and compare predictive power between models. In the additional experiment, the experiment was conducted while changing the number of nodes and layers of the DNN to find the most appropriate number of nodes and layers. In conclusion, as a model with the best performance, the actual transaction price of apartments in 2021 was predicted and compared with the actual data in 2021. Through this, I am confident that machine learning and deep learning will help investors make the right decisions when purchasing homes in various economic situations.


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Cite this article
[IEEE Style]
H. Kim, H. Yoo, H. Oh, "Apartment Price Prediction Using Deep Learning and Machine Learning," KIPS Transactions on Software and Data Engineering, vol. 12, no. 2, pp. 59-76, 2023. DOI: https://doi.org/10.3745/KTSDE.2023.12.2.59.

[ACM Style]
Hakhyun Kim, Hwankyu Yoo, and Hayoung Oh. 2023. Apartment Price Prediction Using Deep Learning and Machine Learning. KIPS Transactions on Software and Data Engineering, 12, 2, (2023), 59-76. DOI: https://doi.org/10.3745/KTSDE.2023.12.2.59.