Statistical and game theoretical approach for combining models
| Project/Area Number |
21700316
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Single-year Grants |
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| Research Field |
Statistical science
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| Research Institution | The University of Tokyo (2010)
The Institute of Physical and Chemical Research (2009) |
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Principal Investigator |
SHIRAISHI Yuichi The University of Tokyo, 医科学研究所, 特任研究員 (70516880)
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| Project Period (FY) |
2009 – 2010
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| Project Status |
Completed (Fiscal Year 2010)
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| Budget Amount *help |
¥3,120,000 (Direct Cost: ¥2,400,000、Indirect Cost: ¥720,000)
Fiscal Year 2010: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2009: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
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| Keywords | 統計的学習理論 / スパース正則化学習 / 多値判別 / 遺伝子発現 / 相乗効果 / バイオインフォマティクス / 統計的検定理論 / マルコフ連鎖モンテカルロ / ensemble learning / stacking / groun lasso / gene regulatory network / state space model |
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| Research Abstract |
A efficient approach for combining binary classifiers for multi-class classification problems was developed. Then, a new statistical method for inferring network from differently stimulated gene expression data was developed. Finally, a rank-based nonparametric statistical test for measuring the synergistic effects between two gene sets was proposed.
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Report
(3 results)
Research Products
(12 results)
