The quantile method for symbolic data analysis.
| Project/Area Number |
25330268
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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 |
Intelligent informatics
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| Research Institution | Tokyo Denki University |
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Principal Investigator |
Ichino Manabu 東京電機大学, 理工学部, 名誉教授 (40057245)
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| Research Collaborator |
BRITO Paula Faculty of Economics of the University of Porto, Associate Professor
UMBLEJA Kadri Tallinn University of Technology, Department of Computer Control
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| Project Period (FY) |
2013-04-01 – 2017-03-31
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| Project Status |
Completed (Fiscal Year 2016)
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| Budget Amount *help |
¥3,120,000 (Direct Cost: ¥2,400,000、Indirect Cost: ¥720,000)
Fiscal Year 2015: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2014: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2013: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
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| Keywords | symbolic data analysis / data mining / Cartesian system model / quantile method / PCA / hierarchical clustering / visualization / regression model / シンボリック・データ・アナリシス / データマイニング / 分位数 / 主成分分析 / 階層的クラスタリング / コンパクトネス / 概念クラスタリング / 累積概念グラフ / データ累積法 / 階層的概念クラスタリング / データ累積グラフ / 重み付き自己情報量 |
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| Outline of Final Research Achievements |
We often use intervals and histograms to summarize the given large numbers of numerical data sets. We use the term symbolic data to call such summarized data and data by the aggregation of different data tables.The quantile method transforms the given symbolic data table to a different sized numerical data table by a unified way. Then, we realize various data analysis methods on the transformed data. This research report includes three quantile methods for symbolic data: (1) A hierarchical method of conceptual clustering; (2) Visualization of multidimensional symbolic data; and (3) The lookup table regression model.
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Report
(5 results)
Research Products
(12 results)
