| Author: | Chan, Elvis |
| Title: | Mavis : an intelligent way to perform mass property valuation through the application of data mining techniques |
| Degree: | M.Sc. |
| Year: | 2002 |
| Subject: | Hong Kong Polytechnic University -- Dissertations Real property -- Valuation Data mining Fuzzy logic |
| Department: | Department of Computing |
| Pages: | 129 leaves : ill. ; 30 cm. |
| Language: | English |
| Abstract: | The purpose of this research is to investigate the merits of applying data mining techniques to the problem of residential property valuation. We present MAVIS, a novel framework for developing a model to estimate the value of residential property for massive development transactions. The system elicits the hidden patterns in the training cases, which could estimate the value of the holdout samples. The adoption of the decision tree technique and fuzzy data mining technique makes MAVIS resilient to noises taken place in real life database, such as missing values and inaccuracy in physical measurements. Without providing user-supplied thresholds to the algorithms, our experimental results showed that MAVIS has been successfully adopted in price estimation and assisting human valuers to make their final decision by eliciting the implicit knowledge and re-applying the non-trivial knowledge to the valuation industry. |
| Rights: | All rights reserved |
| Access: | restricted access |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| b17523473.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 7.54 MB | Adobe PDF | View/Open |
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