2009 Fiscal Year Final Research Report
Establishing the method of rough set clustering
| Project/Area Number |
19300074
|
|---|
| Research Category |
Grant-in-Aid for Scientific Research (B)
|
| Allocation Type | Single-year Grants |
|---|
| Section | 一般 |
|---|
| Research Field |
Sensitivity informatics/Soft computing
|
|---|
| Research Institution | University of Tsukuba |
|---|
Principal Investigator |
MIYAMOTO Sadaaki University of Tsukuba, 大学院・システム情報工学研究科, 教授 (60143179)
|
|---|
| Co-Investigator(Kenkyū-buntansha) |
TSUMOTO Shusaku 島根大学, 医学部, 教授 (10251555)
INUIGUCHI Masahiro 大阪大学, 大学院・基礎工学研究科, 教授 (60193570)
MURAI Tetsuya 北海道大学, 大学院・情報科学研究科, 准教授 (90201805)
|
|---|
| Co-Investigator(Renkei-kenkyūsha) |
HIRANO Shoji 島根大学, 医学部, 准教授 (60333506)
|
|---|
| Project Period (FY) |
2007 – 2009
|
| Keywords | ラフ集合 / 階層的クラスタリング / 一般化ラフ集合 / 情報表 / K-平均法 |
|---|
| Research Abstract |
Traditional rough set theory is concerned with supervised classification of decision tables, with the exception of a few proposals of unsupervised classification, in other words, clustering related to rough sets. However, there are many clustering techniques that had not been applied to rough sets before this study. We have studied theoretical background of clustering for rough sets, and developed a number of new algorithms including both hierarchical and non-hierarchical clustering. We moreover applied the developed methods to a number of data sets including those in medical information. We thus have shown a broad overview of clustering techniques of rough sets and related applications.
|
