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A Randomness Based Analysis on the Data Size Needed for Removing Deceptive Patterns
http://hdl.handle.net/10252/5193
http://hdl.handle.net/10252/51939dad1c83-c541-4446-b517-277bb170a372
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
IEICE_trans. inf.&syst._781-788.pdf (524.3 kB)
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| Item type | 学術雑誌論文 / Journal Article(1) | |||||
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| 公開日 | 2013-11-20 | |||||
| タイトル | ||||||
| タイトル | A Randomness Based Analysis on the Data Size Needed for Removing Deceptive Patterns | |||||
| 言語 | ||||||
| 言語 | eng | |||||
| キーワード | ||||||
| 主題Scheme | Other | |||||
| 主題 | frequent/infrequent item sets | |||||
| キーワード | ||||||
| 主題Scheme | Other | |||||
| 主題 | association rules | |||||
| キーワード | ||||||
| 主題Scheme | Other | |||||
| 主題 | knowledge discovery | |||||
| キーワード | ||||||
| 主題Scheme | Other | |||||
| 主題 | probabilistic analysis | |||||
| 資源タイプ | ||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||
| 資源タイプ | journal article | |||||
| 著者 |
Haraguchi, Kazuya
× Haraguchi, Kazuya× Yagiura, Mitsunori× Boros, Endre× Ibaraki, Toshihide |
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| 著者別名 | ||||||
| 識別子Scheme | WEKO | |||||
| 識別子 | 9993 | |||||
| 姓名 | 原口, 和也 | |||||
| 書誌情報 |
IEICE Transactions on Information and Systems 巻 E91D, 号 3, p. 781-788, 発行日 2008-03 |
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| 出版者 | ||||||
| 出版者 | Institute of Electronics, Information and Communication Engineers | |||||
| ISSN / EISSN | ||||||
| 収録物識別子タイプ | ISSN | |||||
| 収録物識別子 | 0916-8532 | |||||
| DOI | ||||||
| 関連タイプ | isIdenticalTo | |||||
| 識別子タイプ | DOI | |||||
| 関連識別子 | info:doi/10.1093/ietisy/e91-d.3.781 | |||||
| 権利表記 | ||||||
| 権利情報 | Copyright © 2008 The Institute of Electronics, Information and Communication Engineers | |||||
| 出版社版URI | ||||||
| 権利情報 | http://search.ieice.org/ | |||||
| テキストバージョン | ||||||
| 出版タイプ | VoR | |||||
| 出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||
| 日本十進分類法 | ||||||
| 主題Scheme | NDC | |||||
| 主題 | 007 | |||||
| 日本十進分類法 | ||||||
| 主題Scheme | NDC | |||||
| 主題 | 410 | |||||
| NIIサブジェクト | ||||||
| 主題Scheme | Other | |||||
| 主題 | 数学 | |||||
| NIIサブジェクト | ||||||
| 主題Scheme | Other | |||||
| 主題 | 情報学 | |||||
| 抄録 | ||||||
| 内容記述タイプ | Abstract | |||||
| 内容記述 | We consider a data set in which each example is an n-dimensional Boolean vector labeled as true or false. A pattern is a co-occurrence of a particular value combination of a given subset of the variables. If a pattern appears frequently in the true examples and infrequently in the false examples, we consider it a good pattern. In this paper, we discuss the problem of determining the data size needed for removing "deceptive" good patterns; in a data set of a small size, many good patterns may appear superficially, simply by chance, independently of the underlying structure. Our hypothesis is that, in order to remove such deceptive good patterns, the data set should contain a greater number of examples than that at which a random data set contains few good patterns. We justify this hypothesis by computational studies. We also derive a theoretical upper bound on the needed data size in view of our hypothesis. | |||||
