Boundary uncertainty-based classifier evaluation
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DOI[10.14988/00001562]to the data of the same series
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2023-04-26 再収集
2023-04-26 再収集
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- Material Type
- 博士論文
- Author/Editor
- ア, デイビッド
- Author Heading
- Publication Date
- 2019-09-20
- Publication Date (W3CDTF)
- 2019-09-20
- Alternative Title
- 境界曖昧性に基づく分類器評価キョウカイ アイマイセイ ニ モトズク ブンルイキ ヒョウカ
- Degree Grantor
- 同志社大学Doshisha University
- Date Granted
- 2019-09-20
- Date Granted (W3CDTF)
- 2019-09-20
- Dissertation Number
- 甲第1043号
- Degree Type
- 博士(工学)
- Text Language Code
- eng
- Subject Heading
- Target Audience
- 一般
- Note (General)
- 出版タイプ： VoR
- DOI
- 10.14988/00001562
- Persistent ID (NDL)
- info:ndljp/pid/11551562
- Collection
- Collection (Materials For Handicapped People:1)
- Collection (particular)
- 国立国会図書館デジタルコレクション > デジタル化資料 > 博士論文
- Acquisition Basis
- 博士論文（自動収集）
- Format (IMT)
- application/pdf
- Access Restrictions
- 国立国会図書館内限定公開
- Service for the Digitized Contents Transmission Service
- 図書館・個人送信対象外
- Availability of remote photoduplication service
- 可
- Related Material (URI)
- Periodical Title (URI)
- Is Format Of (URI)
- Data Provider (Database)
- 国立国会図書館 : 国立国会図書館デジタルコレクション
- Summary, etc.
- 種々の分類器を対象として，有限個の学習データのみが利用可能である現実においても理論的に的確で計算量的にも実際的な，分類器性能評価手法を提案する．分類器評価における難しさは，有限データのみの利用に起因する分類誤り推定に伴う偏りの発生にある．この困難を解決するため，「境界曖昧性」と呼ばれる新しい評価尺度を提案し，それを用いる評価法の有用性を，3種の分類器と13個のデータセットを用いた実験を通して実証する．We propose a general method that makes accurate evaluation of any classifier model for realistic tasks, both in a theoretical sense despite the finiteness of the available data, and in a practical sense in terms of computation costs. The classifier evaluation challenge arises from the bias of the classification error estimate that is only based on finite data. We bypass this existing difficulty by proposing a new classifier evaluation measure called "boundary uncertainty'' whose estimate based on finite data can be considered a reliable representative of its expectation based on infinite data, and demonstrate the potential of our approach on three classifier models and thirteen datasets.
- DOI
- 10.14988/00001562
- Format (IMT)
- application/pdf
- Source
- 全文/fulltext （fulltext）
- Access Restrictions
- インターネット公開
- Related Material (NCID)
- BC02544595
- Is Format Of
- URI : 掲載刊行物所蔵情報へのリンク ／ Link to Contents
- Data Provider (Database)
- 国立情報学研究所 : 学術機関リポジトリデータベース（IRDB）（機関リポジトリ）
- Original Data Provider (Database)
- 同志社大学 : 同志社大学学術リポジトリ