Forecasting spatial dynamics of the housing market using Support Vector Machine
This paper adopts a novel approach of Support Vector Machine (SVM) to forecast residential housing prices. as one type of machine learning algorithm, the proposed SVM encompasses a larger set of variables that are recognized as price-influencing and meanwhile enables recognizing the geographical pat...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Vilnius Gediminas Technical University
2017-07-01
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| Series: | International Journal of Strategic Property Management |
| Subjects: | |
| Online Access: | https://journals.vgtu.lt/index.php/IJSPM/article/view/1802 |