A Novel Hybrid House Price Prediction Model - EYGİ ERDOĞAN, BİRSEN (My University, 2022)
The real estate sector is evolving and changing rapidly with the increase in housing demand, and new luxury housing projects appear every day. The reliability of housing market investments is largely dependent on accurate pricing.The aim of this study is to introduce a dynamic pricing procedure that estimates house prices using the most important characteristics of a house. For this purpose, a hybrid algorithm using linear regression, clustering analysis, nearest neighbor classification and Support Vector Regression (SVR) method is proposed. Our hybrid algorithm involves using the output of one method as the input of another method for home price prediction to deal with the heteroscedastic nature of the housing data. In other words, the aim of this study is to present a hybrid algorithm that will create different housing clusters from the available data set, classify the houses to which the cluster is unknown, and make price predictions by creating separate prediction models for each class. Housing data collected through manual web scraping of Kadikoy district in Istanbul were used for training and validation of the proposed algorithm. In addition to these data, we validated our algorithm on the KAGGLE house dataset, which covers a wide range of features. The results of the hybrid algorithm were compared using multiple linear regression, Lasso, ridge regression, Support Vector Regression (SVR), AdaBoost, decision tree, random forest and XGBoost regression. Experimental results show that the proposed hybrid model is superior in terms of both Residual Mean Square Error (RMSE), Mean Absolute Value Percent Error (MAPE) and adjusted Rsquare measures for both Kadikoy and KAGGLE housing dataset.
Keywords: Sosyal ve Beşeri Bilimler; İktisat; Çalışma Ekonomisi ve Endüstri ilişkileri; Yönetim ve Çalışma Psikolojisi; Social Sciences and Humanities; Economics; Labor Economics and Industrial Relations; Management and Industrial Psychology; EKONOMİ; Ekonomi ve İş; Sosyal Bilimler (SOC); YÖNETİM; MATEMATİK, İNTERDİSKÜP UYGULAMALAR; Matematik; Temel Bilimler (SCI); ECONOMICS; ECONOMICS & BUSINESS; Social Sciences (SOC); MANAGEMENT; MATHEMATICS, INTERDISCIPLINARY APPLICATIONS; MATHEMATICS; Natural Sciences (SCI); Hesaplamalı Matematik; Analiz; Cebir ve Sayı Teorisi; Matematik (çeşitli); Genel Matematik; Ekonomi ve Ekonometri; Ekonomi, Ekonometri ve Finans (çeşitli); Genel Ekonomi, Ekonometri ve Finans; Karar Bilimleri (çeşitli); Genel Karar Bilimleri; Fizik Bilimleri; Sosyal Bilimler ve Beşeri Bilimler; Computational Mathematics; Analysis; Algebra and Number Theory; Mathematics (miscellaneous); General Mathematics; Economics and Econometrics; Economics, Econometrics and Finance (miscellaneous); General Economics, Econometrics and Finance; Decision Sciences (miscellaneous); General Decision Sciences; Physical Sciences; Social Sciences & Humanities; Housing pricing; Support vector regression; K-means clustering; K-NN classification; DETERMINANTS; REGRESSION; Housing pricing; Support vector regression; K-means clustering; K-NN classification