MISC

2007年

A Spectrum Tree Kernel

Information and Media Technologies
  • Kuboyama Tetsuji
  • ,
  • Hirata Kouichi
  • ,
  • Kashima Hisashi
  • ,
  • Aoki-Kinoshita Kiyoko F.
  • ,
  • Yasuda Hiroshi

2
1
開始ページ
292
終了ページ
299
記述言語
英語
掲載種別
DOI
10.11185/imt.2.292
出版者・発行元
Information and Media Technologies Editorial Board

Learning from tree-structured data has received increasing interest with the rapid growth of tree-encodable data in the World Wide Web, in biology, and in other areas. Our kernel function measures the similarity between two trees by counting the number of shared sub-patterns called tree q-grams, and runs, in effect, in linear time with respect to the number of tree nodes. We apply our kernel function with a support vector machine (SVM) to classify biological data, the glycans of several blood components. The experimental results show that our kernel function performs as well as one exclusively tailored to glycan properties.

リンク情報
DOI
https://doi.org/10.11185/imt.2.292
CiNii Articles
http://ci.nii.ac.jp/naid/130000058330
ID情報
  • DOI : 10.11185/imt.2.292
  • ISSN : 1881-0896
  • CiNii Articles ID : 130000058330
  • identifiers.cinii_nr_id : 1000080302660

エクスポート
BibTeX RIS