Comparison of different machine learning models for mass appraisal of real estate
| dc.authorid | 0000-0002-0881-0396 | |
| dc.authorid | 0000-0002-9725-5792 | |
| dc.contributor.author | Bilgilioğlu, Süleyman Sefa | |
| dc.contributor.author | Yılmaz, Hacı Murat | |
| dc.date.accessioned | 2021-12-14T05:27:49Z | |
| dc.date.available | 2021-12-14T05:27:49Z | |
| dc.date.issued | 2021 | |
| dc.department | Mühendislik Fakültesi | |
| dc.description.abstract | The present study aimed to compare five machine learning techniques, namely, artificial neural network (ANN), support vector machine (SVM), chi-square automatic interaction detection (CHAID), classification and regression tree (CART), and random forest (RF) for mass appraisal of real estate. Firstly, 1982 precedent data was collected throughout the entire study area for train and test models. Secondly, a total of 68 variables were considered for the mass appraisal. Subsequently, the five machine learning techniques were applied. Finally, the receiver operating characteristic (ROC) and various statistical methods were applied to compare five machine learning techniques. | |
| dc.identifier.doi | 10.1080/00396265.2021.1996799 | |
| dc.identifier.endpage | - | en_US |
| dc.identifier.issn | 0039-6265 | |
| dc.identifier.issn | 1752-2706 | |
| dc.identifier.issue | - | en_US |
| dc.identifier.scopusquality | Q2 | |
| dc.identifier.startpage | - | en_US |
| dc.identifier.uri | https:/dx.doi.org/10.1080/00396265.2021.1996799 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12451/8935 | |
| dc.identifier.volume | - | en_US |
| dc.identifier.wos | WOS:000715130600001 | |
| dc.identifier.wosquality | Q4 | |
| dc.indekslendigikaynak | Web of Science | |
| dc.indekslendigikaynak | Scopus | |
| dc.language.iso | en | |
| dc.publisher | Taylor & Francis | |
| dc.relation.ispartof | Survey Review | |
| dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | |
| dc.rights | info:eu-repo/semantics/embargoedAccess | |
| dc.subject | Machine Learning | |
| dc.subject | Mass Appraisal | |
| dc.subject | Artificial Neural Network | |
| dc.subject | Support Vector Machine | |
| dc.subject | Chi-square Automatic Interaction Detection | |
| dc.subject | Classification and Regression Tree | |
| dc.subject | Random Forest | |
| dc.title | Comparison of different machine learning models for mass appraisal of real estate | |
| dc.type | Article |
