Statistical inference in exploratory data analysis and its application
| Project/Area Number |
18K18010
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| Research Category |
Grant-in-Aid for Early-Career Scientists
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| Allocation Type | Multi-year Fund |
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| Review Section |
Basic Section 60030:Statistical science-related
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| Research Institution | Nagasaki University (2020)
Nagoya Institute of Technology (2018-2019) |
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Principal Investigator |
UMEZU Yuta 長崎大学, 情報データ科学部, 准教授 (60793049)
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| Project Period (FY) |
2018-04-01 – 2021-03-31
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| Project Status |
Completed (Fiscal Year 2020)
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| Budget Amount *help |
¥4,160,000 (Direct Cost: ¥3,200,000、Indirect Cost: ¥960,000)
Fiscal Year 2020: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2019: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2018: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
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| Keywords | モデル選択 / selective inference / 高次元漸近理論 / 教師なし学習 / 教師あり学習 / 仮説検定 / スパース正則化法 / 逆強化学習 / パターンマイニング / 統計数学 / 多変量解析 / 探索的データ解析 |
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| Outline of Final Research Achievements |
In recent data science, we often observe data without determining hypothesis to be tested. Particularly, severe selection bias could be occur when the same dataset is used both for generating the hypothesis to be tested and for testing it. Here, in order to correct the selection bias, we focus on the selective inference framework, and tried to improve the existing method. Our main results are the application of the idea of selective inference to unsupervised learning and the development of the method that can be applied to more general class of statistical model by relaxing the normality of the data.
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| Academic Significance and Societal Importance of the Research Achievements |
近年のデータ科学では，検証すべき仮説が定まらないままデータが取得されることが多い．その際，検証すべき仮説の生成と，その仮説の検証を同じデータを用いて行う場合，選択バイアスの問題が生じてしまう．とはいうものの，データの分割や同じ環境での再実験が困難な場合に統計的なエビデンスを提供するためには，同じデータを用いて仮説の生成と検証を行うことが求められる．本研究では，selective inferenceのアイデアに基づき，いろいろな問題に対してこのような統計解析が可能であることを示した．
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Report
(4 results)
Research Products
(20 results)
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[Journal Article] A novel sensitive detection method for DNA methylation in circulating free DNA of pancreatic cancer2020
Author(s)
Shinjo K, Hara K, Nagae G, Umeda T, Katsushima K, Suzuki M, Murofushi Y, Umezu Y, Takeuchi I, Takahashi S, Okuno Y, Matsuo K, Ito H, Tajima S, Aburatani H, Yamao K, Kondo Y.
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Journal Title
PLoS One
Volume: 15
Issue: 6
Pages: 0233782-0233782
DOI
Related Report
Peer Reviewed / Open Access
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[Journal Article] Efficient Learning Algorithm for Sparse SubSequence Pattern-based Classication and Applications to Comparative Animal Trajectory Data Analysis2019
Author(s)
Takuto Sakuma, Kazuya Nishi, Kaoru Kishimoto, Kazuya Nakagawa, Masayuki Karasuyama, Yuta Umezu, Shinsuke Kajioka, Shuhei J. Yamazaki, Koutarou D. Kimura, Sakiko Matsumoto, Ken Yoda, Matasaburo Fukutomi, Hisashi Shidara, Hiroto Ogawa, Ichiro Takeuchi
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Journal Title
Advanced Robotics
Volume: 33
Issue: 3-4
Pages: 134-152
DOI
Related Report
Peer Reviewed / Open Access
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