完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.author | YIN, PY | en_US |
dc.contributor.author | CHEN, LH | en_US |
dc.date.accessioned | 2014-12-08T15:04:08Z | - |
dc.date.available | 2014-12-08T15:04:08Z | - |
dc.date.issued | 1994-02-01 | en_US |
dc.identifier.issn | 0167-8655 | en_US |
dc.identifier.uri | http://hdl.handle.net/11536/2642 | - |
dc.description.abstract | In this paper, a new non-iterative clustering method is proposed. It consists of two passes. In the first pass, the mean distance from one object to its nearest neighbor is estimated. Based on this distance, those noises far away from objects are extracted and removed. In the second pass, the mean distance from the remaining objects to their nearest neighbors is computed. Based on the distance, all the intrinsic clusters are then found. The proposed method is non-iterative and can automatically determine the number of clusters. Experimental results also show that the partition generated by the proposed method is more reasonable than that of the well-known c-means algorithm in many complicated object distributions. | en_US |
dc.language.iso | en_US | en_US |
dc.subject | CLUSTERING | en_US |
dc.subject | C-MEANS ALGORITHM | en_US |
dc.subject | FIXED-RADIUS | en_US |
dc.subject | MEAN MINIMUM DISTANCE | en_US |
dc.subject | NOISE CLUSTER | en_US |
dc.title | A NEW NONITERATIVE APPROACH FOR CLUSTERING | en_US |
dc.type | Article | en_US |
dc.identifier.journal | PATTERN RECOGNITION LETTERS | en_US |
dc.citation.volume | 15 | en_US |
dc.citation.issue | 2 | en_US |
dc.citation.spage | 125 | en_US |
dc.citation.epage | 133 | en_US |
dc.contributor.department | 資訊工程學系 | zh_TW |
dc.contributor.department | Department of Computer Science | en_US |
dc.identifier.wosnumber | WOS:A1994MV78400003 | - |
dc.citation.woscount | 22 | - |
顯示於類別: | 期刊論文 |