Classification of large scale qualitative data and visualization of their structure.
| Project/Area Number |
23500340
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Statistical science
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| Research Institution | Hokkaido University |
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Principal Investigator |
IMAI Hideyuki 北海道大学, 情報科学研究科, 教授 (10213216)
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| Co-Investigator(Kenkyū-buntansha) |
KUDO Mineichi 北海道大学, 大学院・情報科学研究科, 教授 (60205101)
TANAKA Akira 北海道大学, 大学院・情報科学研究科, 准教授 (20332471)
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| Project Period (FY) |
2011 – 2013
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| Project Status |
Completed (Fiscal Year 2013)
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| Budget Amount *help |
¥5,200,000 (Direct Cost: ¥4,000,000、Indirect Cost: ¥1,200,000)
Fiscal Year 2013: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2012: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2011: ¥2,080,000 (Direct Cost: ¥1,600,000、Indirect Cost: ¥480,000)
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| Keywords | クラスタリング / ネットワーク / 正則化 / 変数選択 / 標本化定理 / グラフ構造 / 大規模データ |
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| Research Abstract |
To perform knowledge discovery from large data sets as signals from various sensors or texts accumulated in the web, it is required to classify into groups which have some common attribute as a pretreatment for detailed analysis even for such large and irregular data sets. Though such data sets contain a large number of items, it is often sufficient to use a small number of items for reasonable classification. We have studied mainly variable selection and regularization method for classification of qualitative data both from theoretical analysis and numerical experiments. These results have applied to the system for estimating human behavior using the data from the infrared sensors placed in the ceiling of the room.
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Report
(4 results)
Research Products
(33 results)
