結合灰色關聯分析與不同權重合成的房價預測

Combine Grey Relational Analysis and Various Weighted Synthesis for Housing Price Prediction

陳威膨(Wei-Peng Tan)

指導教授 ： 周宗南

朝陽科技大學/管理學院/財務金融系/碩士(2016年)

摘要

無資料

關鍵字

房價預測

並列摘要

The objective of this paper is to evaluate the performance of the grey relational analysis in predicting the housing price for the real estate market of Taiwan. An instance-based approach which used k-nearest neighbor classifier was also applied for performance comparison. The grey relational analysis was modified to calculate the weighted synthesis of the top ten matching instances through various weighting strategies. The experimental results in this paper concluded that the grey relational analysis outperformed the instance-based approach in terms of the mean absolute error, root mean square error and relative absolute error. In addition, the synthesis strategy with descending weights performed better than the averaging weights during the integration process of matching instances. The result also suggested that the performance was slightly decreased if the top ten matching instances was reduced to five instances.
The grey relational analysis integrated with the weighted synthesis model can assist both buyers and owners in identifying opportunities and estimating the potential risks in a worsening real estate market.

並列關鍵字

Housing Price Prediction

參考文獻

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