摘要
Feature (Gene) selection is a frequently used preprocessing technology for successful cancer classification task in microarray gene expression data analysis. Widely used gene selection approaches are mainly focused on the filter methods. Filter methods are usually considered to be very effective and efficient for high-dimensional data. This paper reviews the existing filter methods, and shows the performance of the representative algorithms on microarray data by extensive experimental study. Surprisingly, the experimental results show that filter methods are not very effective on microarray data. We analyze the cause of the result and provide the basic ideas for potential solutions.
| 源语言 | 英语 |
|---|---|
| 主期刊名 | Proceedings - 2007 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW |
| 出版商 | Institute of Electrical and Electronics Engineers Inc. |
| 页 | 97-100 |
| 页数 | 4 |
| ISBN(印刷版) | 9781424416042 |
| DOI | |
| 出版状态 | 已出版 - 2007 |
| 活动 | 2007 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW - San Jose, CA, 美国 期限: 2 11月 2007 → 4 11月 2007 |
出版系列
| 姓名 | Proceedings - 2007 IEEE International Conference on Bioinformaticsand Biomedicine Workshops, BIBMW |
|---|
会议
| 会议 | 2007 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW |
|---|---|
| 国家/地区 | 美国 |
| 市 | San Jose, CA |
| 时期 | 2/11/07 → 4/11/07 |
联合国可持续发展目标
此成果有助于实现下列可持续发展目标:
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可持续发展目标 3 良好健康与福祉
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