| Modified Sequential Floating Search Algorithm with a Novel Ranking Method | |
|---|---|
| 學年 | 100 |
| 學期 | 2 |
| 出版（發表）日期 | 2012-03-01 |
| 作品名稱 | Modified Sequential Floating Search Algorithm with a Novel Ranking Method |
| 作品名稱（其他語言） | |
| 著者 | Chou, Chien-Hsing; Hsieh, Yi-Zeng; Tsai, Chi-Yi |
| 單位 | 淡江大學電機工程學系 |
| 出版者 | Kumamoto: I C I C International |
| 著錄名稱、卷期、頁數 | International Journal of Innovative Computing, Information and Control 8(3)pt.B, pp.2089-2010 |
| 摘要 | Feature selection plays a critical role in pattern classification. Of the various feature selection methods, the sequential floating search (SFS) method is perhaps the most well-known and widely adopted. This paper proposes a feature selection method combining feature ranking and SFS. The proposed feature ranking approach adopts the new idea of false features to rank features based on their importance, and then applies SFS to features that are less important or of lower rank. This approach overcomes issues with the original SFS and extracts more critical features. In addition, most feature selection methods do not consider the problem of multi-class classification. As a result, these methods have difficulty achieving good performance when dealing with a greater variety of classes. Therefore, this study adopts a one-against-all strategy to address this issue. The proposed approach divides multi-class classification into several binary classifications and adopts feature selection to derive individual feature subsets. This strategy achieves satisfactory performance in experimental simulations. |
| 關鍵字 | Feature selection; Sequential floating search; False feature; One-against-all; Pattern classification |
| 語言 | en |
| ISSN | 1349-4198 |
| 期刊性質 | 國外 |
| 收錄於 | SCI EI |
| 產學合作 | |
| 通訊作者 | |
| 審稿制度 | |
| 國別 | JPN |
| 公開徵稿 | |
| 出版型式 | 紙本 |
| 相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/76273 ) |
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