A Clustering-Based Algorithm for Data Reduction
5th International Workshop on Computational Intelligence & Applications Proceedings : IWCIA 2009
65-70 頁
2009-11 発行
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この文献の参照には次のURLをご利用ください : https://ir.lib.hiroshima-u.ac.jp/00028454
| ファイル情報(添付) | |
| タイトル ( eng ) |
A Clustering-Based Algorithm for Data Reduction
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| 作成者 |
Yeh Chi-Yuan
Ouyang Jeng
Lee Shie-Jue
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| 収録物名 |
5th International Workshop on Computational Intelligence & Applications Proceedings : IWCIA 2009
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| 開始ページ | 65 |
| 終了ページ | 70 |
| 抄録 |
Finding an efficient data reduction method for largescale problems is an imperative task. In this paper, we propose a similarity-based self-constructing fuzzy clustering algorithm to do the sampling of instances for the classification task. Instances that are similar to each other are grouped into the same cluster. When all the instances have been fed in, a number of clusters are formed automatically. Then the statistical mean for each cluster will be regarded as representing all the instances covered in the cluster. This approach has two advantages. One is that it can be faster and uses less storage memory. The other is that the number of new representative instances need not be specified in advance by the user. Experiments on real-world datasets show that our method can run faster and obtain better reduction rate than other methods.
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| 著者キーワード |
Large-scale dataset
fuzzy similarity
data reduction
prototype reduction
instance-filtering
instance-abstraction
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| NDC分類 |
技術・工学 [ 500 ]
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| 言語 |
英語
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| 資源タイプ | 会議発表論文 |
| 出版者 |
IEEE SMC Hiroshima Chapter
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| 発行日 | 2009-11 |
| 権利情報 |
(c) Copyright by IEEE SMC Hiroshima Chapter.
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| 出版タイプ | Version of Record（出版社版。早期公開を含む） |
| アクセス権 | オープンアクセス |
| 収録物識別子 |
[ISSN] 1883-3977
[URI] http://www.hil.hiroshima-u.ac.jp/iwcia/2009/
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