2020
DOI: 10.35808/ersj/1740
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Parametric and Non-parametric Methods in Mass Appraisal on Poorly Developed Real Estate Markets*

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Cited by 9 publications
(7 citation statements)
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“…Whilst ML models generally perform better than MLR since they can identify complex relationships and do not suffer from overfitting or multicollinearity, where data is limited, they can be outperformed simply due to insufficient data to make precise predictions. These results are also supported by Gnat & Doszyn's findings which were discussed previously [12]. Due to the size of the Paphos market, and the accuracy provided regarding long-term rental properties, acquiring sufficient data to achieve higher-performing ML models would be difficult since through extensive market research almost 50% of the properties advertised were not suitable.…”
Section: Optimal Strategysupporting
confidence: 77%
See 1 more Smart Citation
“…Whilst ML models generally perform better than MLR since they can identify complex relationships and do not suffer from overfitting or multicollinearity, where data is limited, they can be outperformed simply due to insufficient data to make precise predictions. These results are also supported by Gnat & Doszyn's findings which were discussed previously [12]. Due to the size of the Paphos market, and the accuracy provided regarding long-term rental properties, acquiring sufficient data to achieve higher-performing ML models would be difficult since through extensive market research almost 50% of the properties advertised were not suitable.…”
Section: Optimal Strategysupporting
confidence: 77%
“…Further to this, Limsombunchai, Gan, & Lee were able to achieve an R-Squared value of 0.75 with only 200 data points which demonstrates that even smaller sample sizes can be used to effectively create MLR models [11]. Interestingly, a study carried out that investigated developing markets with limited data found that MLR models outperformed both k-NN and RF regarding the mean absolute percentage errors (MAPE) [12]. The study used 318 data points from Szczecin in Poland, which is far less developed than Paphos and does not attract the same level of tourism.…”
Section: Data Collectionmentioning
confidence: 84%
“…Furthermore, Limsombunchai, Gan, and Lee were able to achieve an Rsquared value of 0.75 with only 200 data points, which demonstrates that even smaller sample sizes can be used to effectively create MLR models [25]. Interestingly, one study that investigated developing markets with limited data found that MLR models outperformed both the k-NN and RF methods regarding their mean absolute percentage errors (MAPEs) [26]. The study used 318 data points from Szczecin in Poland, which is far less developed than Paphos and does not attract the same level of tourism.…”
Section: Data Collectionmentioning
confidence: 98%
“…Ridge regression in real estate appraisal models was considered in (Newell, 1982;Anderson, 1981;Moore et al, 1984). The application of multiple regression and machine learning methods in real estate mass appraisal was presented in (Gnat & Doszyń, 2020). In this article, the regularization of ridge regression was also applied.…”
Section: Literature Reviewmentioning
confidence: 99%