Please use this identifier to cite or link to this item:
https://ah.lib.nccu.edu.tw/handle/140.119/70631
題名: | Building a Cost-constrained Decision Tree with Mulitiple Condition Attributes | 作者: | 唐揆 Tang, Kwei |
貢獻者: | 企管系 | 關鍵詞: | Data mining; Decision analysis; Cost-sensitive learning; Classification; Decision tree | 日期: | 2009 | 上傳時間: | 16-Oct-2014 | 摘要: | Costs are often an important part of the classification process. Cost factors have been taken into consideration in many previous studies regarding decision tree models. In this study, we also consider a cost-sensitive decision tree construction problem. We assume that there are test costs that must be paid to obtain the values of the decision attribute and that a record must be classified without exceeding the spending cost threshold. Unlike previous studies, however, in which records were classified with only a single condition attribute, in this study, we are able to simultaneously classify records with multiple condition attributes. An algorithm is developed to build a cost-constrained decision tree, which allows us to simultaneously classify multiple condition attributes. The experimental results show that our algorithm satisfactorily handles data with multiple condition attributes under different cost constraints. | 關聯: | Information Sciences, 179(7), 967-979 | 資料類型: | article | DOI: | http://dx.doi.org/10.1016/j.ins.2008.11.032 |
Appears in Collections: | 期刊論文 |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
967979.pdf | 537.69 kB | Adobe PDF2 | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.