Feature Selection in Large Scale Data Stream for Credit Card Fraud Detection
5th International Workshop on Computational Intelligence & Applications Proceedings : IWCIA 2009
202-207 頁
2009-11 発行
アクセス数 : 583 件
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今月のダウンロード数 : 3 件
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/00028424
| ファイル情報(添付) | |
| タイトル ( eng ) |
Feature Selection in Large Scale Data Stream for Credit Card Fraud Detection
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| 作成者 |
Ise Masayuki
Niimi Ayahiko
Konishi Osamu
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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 | 202 |
| 終了ページ | 207 |
| 抄録 |
There is increased interest in accurate model acquisition from large scale data streams. In this paper, because we have focused attention on time-oriented variation, we propose a method contracting time-series data for data stream. Additionally, our proposal method employs the combination of plural simple contraction method and original features. In this experiment, we treat a real data stream in credit card transactions because it is large scale and difficult to classify. This experiment yields that this proposal method improves classification performance according to training data. However, this proposal method needs more generality. Hence, we'll improve generality with employing the suitable combination of a contraction method and a feature for the feature in our proposal method.
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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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