A Comparison of Multiple Linear Regression and Random Forest Regression to Evaluate the Price of Residential Units (Case Study: North Valiasr, Tabriz)
One of the most fundamental aspects of any country is the housing economy. Because its price changes will cause numerous effects on the national economy in the short and long periods; therefore, it is essential to obtain a model which can assess housing prices. In this regard, the objectives of this...
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| Format: | Article |
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University of Sistan and Baluchistan
2021-09-01
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| Series: | جغرافیا و آمایش شهری منطقه‌ای |
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| Online Access: | https://gaij.usb.ac.ir/article_6486_d6bac030d4e36d8531f259f676b419df.pdf |
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| author | Mohammad Ali Kooshesh Vatan Akbar Asghari Zamani Mohammad Nemati Firooz Poormohammad |
| author_facet | Mohammad Ali Kooshesh Vatan Akbar Asghari Zamani Mohammad Nemati Firooz Poormohammad |
| author_sort | Mohammad Ali Kooshesh Vatan |
| collection | DOAJ |
| description | One of the most fundamental aspects of any country is the housing economy. Because its price changes will cause numerous effects on the national economy in the short and long periods; therefore, it is essential to obtain a model which can assess housing prices. In this regard, the objectives of this research are to compare multiple linear regression and random forest regression to evaluate the price of residential units and extract the important factors in relation to the price of them. The statistical population included four north valiasr neighborhoods (n=30,272 units) and the sample size was estimated to be 379 units using the cochran formula at 95% confidence level and with a 5% error. But 400 samples considered. To eliminate the effect of time, only the data of september, 2020 were used. Also, arcmap, spss and rstudio software were used to analyze the data. According to the results, area, apartment floors, construction year, proximity to health centers, urban facilities, green spaces, religious land-use, medical centers, military land-uses and floor level, are the ten most important variables in relation to housing prices in the north valiasr neighborhoods, respectively. Further, according to the findings, random forest regression has a superior capability in predicting housing prices in north valiasr of tabriz compared to multiple linear regression. |
| first_indexed | 2024-03-13T04:02:21Z |
| format | Article |
| id | doaj.art-a74566afc2624c2299ba1d11dcc671e9 |
| institution | Directory Open Access Journal |
| issn | 2345-2277 2783-5278 |
| language | fas |
| last_indexed | 2024-03-13T04:02:21Z |
| publishDate | 2021-09-01 |
| publisher | University of Sistan and Baluchistan |
| record_format | Article |
| series | جغرافیا و آمایش شهری منطقه‌ای |
| spelling | doaj.art-a74566afc2624c2299ba1d11dcc671e92023-06-21T10:58:17ZfasUniversity of Sistan and Baluchistanجغرافیا و آمایش شهری منطقه‌ای2345-22772783-52782021-09-011140578210.22111/gaij.2021.64866486A Comparison of Multiple Linear Regression and Random Forest Regression to Evaluate the Price of Residential Units (Case Study: North Valiasr, Tabriz)Mohammad Ali Kooshesh Vatan0Akbar Asghari Zamani1Mohammad Nemati2Firooz Poormohammad3دانشجوی دکتری جغرافیا و برنامه‌‌ریزی شهری، دانشکده برنامه‌‌ریزی و علوم محیطی، دانشگاه تبریزدانشیار گروه جغرافیا و برنامه‌‌ریزی شهری، دانشکده برنامه‌‌ریزی و علوم محیطی، دانشگاه تبریزدانشجوی دکتری جغرافیا و برنامه‌‌ریزی شهری، دانشکده برنامه‌‌ریزی و علوم محیطی، دانشگاه تبریزکارشناسی ارشد جغرافیا و برنامه‌‌ریزی شهری، دانشگاه تبریزOne of the most fundamental aspects of any country is the housing economy. Because its price changes will cause numerous effects on the national economy in the short and long periods; therefore, it is essential to obtain a model which can assess housing prices. In this regard, the objectives of this research are to compare multiple linear regression and random forest regression to evaluate the price of residential units and extract the important factors in relation to the price of them. The statistical population included four north valiasr neighborhoods (n=30,272 units) and the sample size was estimated to be 379 units using the cochran formula at 95% confidence level and with a 5% error. But 400 samples considered. To eliminate the effect of time, only the data of september, 2020 were used. Also, arcmap, spss and rstudio software were used to analyze the data. According to the results, area, apartment floors, construction year, proximity to health centers, urban facilities, green spaces, religious land-use, medical centers, military land-uses and floor level, are the ten most important variables in relation to housing prices in the north valiasr neighborhoods, respectively. Further, according to the findings, random forest regression has a superior capability in predicting housing prices in north valiasr of tabriz compared to multiple linear regression.https://gaij.usb.ac.ir/article_6486_d6bac030d4e36d8531f259f676b419df.pdfhousing pricemultiple linear regressionrandom forest regressionnorth valiasrtabriz |
| spellingShingle | Mohammad Ali Kooshesh Vatan Akbar Asghari Zamani Mohammad Nemati Firooz Poormohammad A Comparison of Multiple Linear Regression and Random Forest Regression to Evaluate the Price of Residential Units (Case Study: North Valiasr, Tabriz) جغرافیا و آمایش شهری منطقه‌ای housing price multiple linear regression random forest regression north valiasr tabriz |
| title | A Comparison of Multiple Linear Regression and Random Forest Regression to Evaluate the Price of Residential Units (Case Study: North Valiasr, Tabriz) |
| title_full | A Comparison of Multiple Linear Regression and Random Forest Regression to Evaluate the Price of Residential Units (Case Study: North Valiasr, Tabriz) |
| title_fullStr | A Comparison of Multiple Linear Regression and Random Forest Regression to Evaluate the Price of Residential Units (Case Study: North Valiasr, Tabriz) |
| title_full_unstemmed | A Comparison of Multiple Linear Regression and Random Forest Regression to Evaluate the Price of Residential Units (Case Study: North Valiasr, Tabriz) |
| title_short | A Comparison of Multiple Linear Regression and Random Forest Regression to Evaluate the Price of Residential Units (Case Study: North Valiasr, Tabriz) |
| title_sort | comparison of multiple linear regression and random forest regression to evaluate the price of residential units case study north valiasr tabriz |
| topic | housing price multiple linear regression random forest regression north valiasr tabriz |
| url | https://gaij.usb.ac.ir/article_6486_d6bac030d4e36d8531f259f676b419df.pdf |
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