銀行房屋貸款業務中，房屋鑑價是房貸一個重要且複雜的環節，因房屋本身及周遭條件的差異，座落同一區域的房屋單價會有高低落差，故價格的鑑定並不容易。鑑價工作大多仰賴專業的鑑價師分析鑑定，但許多銀行因作業時間與成本限制下，皆為內部自行鑑價，因此易產生作業風險。本研究希望能解決銀行目前鑑價問題，經由資料探勘數值預測的方式，利用銀行內部不動產鑑價資料建立一套預測房屋價格的模型，期望由此模型中不同屬性的分析，提供銀行於辦理不動產鑑價時，能確實評估該筆擔保品之鑑估金額、簡化房屋的鑑價流程、縮短鑑價時間，使鑑價結果讓銀行有客觀公正的參考的依據。另一方面使用內政部實價登錄資料進行預測作為對照，比較實價登錄與銀行鑑價兩者的異同處，進而達到鑑價的完整性與準確性的目的。研究結果顯示，使用模式樹預測的結果優於線性迴歸分析，實價登錄與銀行鑑價皆重視的屬性有鄉鎮市區、臨路狀況、標的物總面積，不同處在於實價登錄較重視建物型態、銀行鑑價較為重視屋齡。而實價登錄資料可以直接用模式樹較準確的預測房屋的價格，銀行鑑價必須先執行分群方法後再使用模式樹才能得到較佳的預測結果。

Real estate appraisal is a complex task owing to the widely differing geographic factors of residential properties. If a bank does not hire a professional appraiser, it might become a subject to higher risk. By means of data mining, this research utilizes the real estate appraisal data of a bank to induce a model for predicting housing prices. Another predictive model learned from the actual selling prices collected from the Department of Land Administration, which is a part of the Ministry of the Interior in Taiwan, is also generated for comparison. The experimental results show that model tree can have a less mean absolute error than linear regression. Moreover, both actual selling prices and the bank appraisal depend on location, road conditions, and the total area of a house. A greater emphasis is placed on the building type for determining the actual price, while bank appraisals place a greater emphasis on the age of a building.

書籍
Olson, David L. & Shi, Yong, (2008). 資料探勘, 美商麥格羅‧希爾國際股分有限公司 台灣分公司, 台北市
邢進文, (民國93年), 不動產投資經營與估價分析, 五南圖書出版股份有限公司, 台北市
卓輝華, (民國99年) , 不動產估價, 五南圖書出版股份有限公司, 台北市
梁榮輝、謝明瑞、莊孟翰、黃建森, (民國96年), 不動產估價實務, 國立空中大學, 新北縣蘆洲區
陳瑞、周林毅, (民國96年) , 風險評估與決策管理, 五南圖書出版股份有限公司, 台北市
楊鴻謙、徐士堯, (民國94年), 不動產經紀法規實務與理論, 一品文化出版社, 台北市
銀行授信實務概要編輯委員會, (民國97年) , 銀行授信實務概要, 臺灣金融研訓院, 台北市
賴碧瑩, (民國98年) , 現代不動產估價,智勝文化事業有限公司, 台北市
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