2012 Fiscal Year Final Research Report
Integration of Statistics and Machine Learning for Combining Prediction, Knowledge Discovery and Inference.
| Project/Area Number |
20240028
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| Research Category |
Grant-in-Aid for Scientific Research (A)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Statistical science
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| Research Institution | The Institute of Statistical Mathematics |
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Principal Investigator |
EGUCHI Shinto 統計数理研究所, 数理・推論研究系, 教授 (10168776)
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| Co-Investigator(Kenkyū-buntansha) |
KURIKI Satoshi 統計数理研究所, 数理・推論研究系, 教授 (90195545)
FUJISAWA Hironori 統計数理研究所, 数理・推論研究系, 准教授 (00301177)
HENMI Masayuki 統計数理研究所, 数理・推論研究系, 准教授 (80465921)
MATSUURA Masaaki (公財)がん研究会, ゲノムセンター情報解析部門, 部門長 (40173794)
MANO Shuhei 統計数理研究所, 数理・推論研究系, 准教授 (20372948)
KOMORI Osamu 統計数理研究所, 統計思考院, 特任助教 (60586379)
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| Co-Investigator(Renkei-kenkyūsha) |
TAKENOUCHI Takashi はこだて未来大学, 複雑系情報学科, 准教授 (50403340)
KAWAKITA Masanori 九州大学, システム情報科学研究科, 助教 (90435496)
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| Project Period (FY) |
2008 – 2012
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| Keywords | 分類 / パターン認識 |
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| Research Abstract |
Statistical methods to achieve scientific results conducted from genomics and omics data have been exploited. In particular, for prediction of phenotypes (disease type, treatment effect, prognosis) we enhanced to implement several proposals by a fusion between statistics and machine learning. The boosting method by maximization of Area Under Curve is applied to gene expression data. LASSO clustering is proposed to select genes for detecting subtypes in breast cancer patients.
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