A Discretization Algorithm of Continuous Attributes Based on Supervised Clustering
文献类型：会议论文
| 作者 | Hua HY(花海洋) ; Zhao HC(赵怀慈)
|
| 出版日期 | 2009 |
| 会议名称 | Chinese Conference on Pattern Recognition/1st CJK Joint Workshop on Pattern Recognition |
| 会议日期 | November 4-6, 2009 |
| 会议地点 | Nanjing, China |
| 关键词 | Data mining discretization classification supervised clustering |
| 页码 | 40307 |
| 中文摘要 | Many machine learning algorithms can be applied only to data described by categorical attributes. So discretizatioti of continuous attributes is one of the important steps in preprocessing of extracting knowledge. Traditional discretization algorithms based on clustering need a pre-determined clustering number k, also typically are applied in an unsupervised learning framework. This paper describes such an algorithm, called SX-means (Supervised X-means), which is a new algorithm of supervised discretization of continuous attributes on clustering. The algorithm modifies clusters with knowledge of the class distribution dynamically. And this procedure can not stop until the proper k is found. For the number of clusters k is not pre-determined by the user and class distribution is applied, the random of result is decreased greatly. Experimental evaluation of several discretization algorithms on six artificial data sets show that the proposed algorithm is more efficient and can generate a better discretization schema. Comparing the output of C4.5, resulting tree is smaller, less classification rules, and high accuracy of classification. |
| 收录类别 | EI ; CPCI（ISTP） |
| 产权排序 | 1 |
| 会议录 | PROCEEDINGS OF THE 2009 CHINESE CONFERENCE ON PATTERN RECOGNITION AND THE FIRST CJK JOINT WORKSHOP ON PATTERN RECOGNITION, VOLS 1 AND 2
 |
| 会议录出版者 | IEEE |
| 会议录出版地 | NEW YORK |
| 语种 | 英语 |
| ISBN号 | 978-1-4244-4199-0 |
| WOS记录号 | WOS:000278039800002 |
| 源URL | [http://ir.sia.cn/handle/173321/7936]  |
| 专题 | 沈阳自动化研究所_光电信息技术研究室 |
| 推荐引用方式 GB/T 7714 | Hua HY,Zhao HC. A Discretization Algorithm of Continuous Attributes Based on Supervised Clustering[C]. 见:Chinese Conference on Pattern Recognition/1st CJK Joint Workshop on Pattern Recognition. Nanjing, China. November 4-6, 2009. |
入库方式： OAI收割
来源：沈阳自动化研究所
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