این سایت در حال حاضر پشتیبانی نمی شود و امکان دارد داده های نشریات بروز نباشند
Iranian Economic Review، جلد ۲۷، شماره ۴، صفحات ۱۲۸۵-۱۳۰۶
عنوان فارسی
چکیده فارسی مقاله
کلیدواژه‌های فارسی مقاله
عنوان انگلیسی House Price Prediction Model Selection Based on Lorenz and Concentration Curves: Empirical Evidence from Tehran House Market
چکیده انگلیسی مقاله This study provides a selection of the house price prediction model for the Tehran city based on the area between the Lorenz curve (LC) and the concentration curve (CC) of the forecast price using 206,556 observed transaction data from March 21, 2018, to February 19, 2021. Several different methods such as generalized linear models (GLM) and recursive partitioning and regression trees (RPART), random forests (RF) regression models, and neural network (NN) models for predicting housing prices. We used 90% of all randomly selected data samples to estimate the parameters of pricing models and 10% of the remaining data sets to test the accuracy of the prediction. The results showed that the area between the LC and CC curves (known as the ABC criterion) of reals and forecast prices in the test data sample of the random forest regression model was less than that of other models examined. The comparison of the calculated ABC criteria leads us to conclude that the nonlinear regression, like the RF regression model, provides an accurate prediction of housing prices in Tehran City.
کلیدواژه‌های انگلیسی مقاله ABC Criteria, City of Tehran, Concentration Curves, House Features, Housing price, Model Selection Metrics, Price Prediction Models
نویسندگان مقاله Mohammad Mirbagherijam |
Department of Economics, Shahrood University of Technology, Shahrood, Iran

نشانی اینترنتی https://ier.ut.ac.ir/article_94936_689794ca30d236e183d525d12557ee4f.pdf
فایل مقاله فایلی برای مقاله ذخیره نشده است
کد مقاله (doi)
زبان مقاله منتشر شده en
موضوعات مقاله منتشر شده
نوع مقاله منتشر شده
برگشت به: صفحه اول پایگاه   |   نسخه مرتبط   |   نشریه مرتبط   |   فهرست نشریات