Interpretable machine learning approaches to high-dimensional data and their applications to biomedical engineering problems

京都大学 === 0048 === 新制・課程博士 === 博士(情報学) === 甲第21215号 === 情博第668号 === 新制||情||115(附属図書館) === 京都大学大学院情報学研究科システム科学専攻 === (主査)教授石井信, 教授下平英寿, 教授加納学, 銅谷賢治 === 学位規則第4条第1項該当 === Doctor of Informatics === Kyoto University === DFAM...

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Bibliographic Details
Main Author:	Yoshida, Kosuke
Other Authors:	石井, 信
Format:	Doctoral Thesis
Language:	English
Published:	Kyoto University 2018
Subjects:	machine learning high-dimensional data biomedical engineering depression fMRI kernel method 007
Online Access:	http://hdl.handle.net/2433/232416

id	ndltd-kyoto-u.ac.jp-oai-repository.kulib.kyoto-u.ac.jp-2433-232416
record_format	oai_dc
spelling	ndltd-kyoto-u.ac.jp-oai-repository.kulib.kyoto-u.ac.jp-2433-2324162021-09-06T05:12:01Z Interpretable machine learning approaches to high-dimensional data and their applications to biomedical engineering problems 高次元データへの解釈可能な機械学習アプローチとその医用工学問題への適用 Yoshida, Kosuke 石井, 信下平, 英寿加納, 学銅谷, 賢治吉田, 光佑ヨシダ, コウスケ machine learning high-dimensional data biomedical engineering depression fMRI kernel method 007 京都大学 0048 新制・課程博士博士(情報学) 甲第21215号情博第668号新制\|\|情\|\|115(附属図書館) 京都大学大学院情報学研究科システム科学専攻 (主査)教授石井信, 教授下平英寿, 教授加納学, 銅谷賢治学位規則第4条第1項該当 Doctor of Informatics Kyoto University DFAM 2018-06-22T09:39:03Z 2018-06-22T09:39:03Z 2018-03-26 2018-03-26 doctoral thesis Thesis or Dissertation http://hdl.handle.net/2433/232416 14301甲第21215号 10.14989/doctor.k21215 14301 eng application/pdf Kyoto University 京都大学
collection	NDLTD
language	English
format	Doctoral Thesis
sources	NDLTD
topic	machine learning high-dimensional data biomedical engineering depression fMRI kernel method 007
spellingShingle	machine learning high-dimensional data biomedical engineering depression fMRI kernel method 007 Yoshida, Kosuke Interpretable machine learning approaches to high-dimensional data and their applications to biomedical engineering problems
description	京都大学 === 0048 === 新制・課程博士 === 博士(情報学) === 甲第21215号 === 情博第668号 === 新制\|\|情\|\|115(附属図書館) === 京都大学大学院情報学研究科システム科学専攻 === (主査)教授石井信, 教授下平英寿, 教授加納学, 銅谷賢治 === 学位規則第4条第1項該当 === Doctor of Informatics === Kyoto University === DFAM
author2	石井, 信
author_facet	石井, 信 Yoshida, Kosuke
author	Yoshida, Kosuke
author_sort	Yoshida, Kosuke
title	Interpretable machine learning approaches to high-dimensional data and their applications to biomedical engineering problems
title_short	Interpretable machine learning approaches to high-dimensional data and their applications to biomedical engineering problems
title_full	Interpretable machine learning approaches to high-dimensional data and their applications to biomedical engineering problems
title_fullStr	Interpretable machine learning approaches to high-dimensional data and their applications to biomedical engineering problems
title_full_unstemmed	Interpretable machine learning approaches to high-dimensional data and their applications to biomedical engineering problems
title_sort	interpretable machine learning approaches to high-dimensional data and their applications to biomedical engineering problems
publisher	Kyoto University
publishDate	2018
url	http://hdl.handle.net/2433/232416
work_keys_str_mv	AT yoshidakosuke interpretablemachinelearningapproachestohighdimensionaldataandtheirapplicationstobiomedicalengineeringproblems AT yoshidakosuke gāocìyuándētahenojiěshìkěnéngnajīxièxuéxíapurōchitosonoyīyònggōngxuéwèntíhenoshìyòng
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Interpretable machine learning approaches to high-dimensional data and their applications to biomedical engineering problems

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