Development of a high dimensional aggregation operator and its application to a clustering model
Project/Area Number |
20500252
|
Research Category |
Grant-in-Aid for Scientific Research (C)
|
Allocation Type | Single-year Grants |
Section | 一般 |
Research Field |
Statistical science
|
Research Institution | University of Tsukuba |
Principal Investigator |
ILIC Mika University of Tsukuba, 大学院・システム情報工学研究科, 准教授 (60269214)
|
Co-Investigator(Renkei-kenkyūsha) |
SHIMIZU Nobuo 統計数理研究所, 助教 (00332130)
|
Project Period (FY) |
2008 – 2010
|
Project Status |
Completed (Fiscal Year 2010)
|
Budget Amount *help |
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2010: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2009: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2008: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
|
Keywords | 分類 / パターン認識 / Aggregation Operator / クラスタリング / ソフトコンピューティング / カーネル法 / 高次元データ / Alignment / クラスタリングモデル / PCA / ソフコンピューティング |
Research Abstract |
This research proposed a high dimensional aggregation operator and investigated its features. In addition, we applied this aggregation operator to a clustering model for practical use. Conventionally, research based on statistical metric space has been discussed for this area, however a generalized high dimensional aggregation operator has not been proposed. So, in this research, we developed a high dimensional aggregation operator to obtain a general purpose clustering model by exploiting this aggregation operator.
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Report
(4 results)
Research Products
(45 results)