Semi-supervised classification with spectral subspace projection of data

Weiwei Du, Kiichi Urahama

研究成果: Contribution to journalArticle査読

2 被引用数 (Scopus)

抄録

A semi-supervised classification method is presented. A robust unsupervised spectral mapping method is extended to a semi-supervised situation. Our proposed algorithm is derived by linearization of this nonlinear semi-supervised mapping method. Experiments using the proposed method for some public benchmark data reveal that our method outperforms a supervised algorithm using the linear discriminant analysis for the iris and wine data and is also more accurate than a semi-supervised algorithm of the logistic GRF for the ionosphere dataset.

本文言語英語
ページ(範囲)374-377
ページ数4
ジャーナルIEICE Transactions on Information and Systems
E90-D
1
DOI
出版ステータス出版済み - 1 1 2007

All Science Journal Classification (ASJC) codes

  • Software
  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering
  • Artificial Intelligence

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