Evaluations of a multiple SOMs method for estimating missing values

Kouki Arima, Nobuhiro Okada, Yasutaka Tsuji, Kazuo Kiguchi

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

3 被引用数 (Scopus)

抄録

Data mining, which is a technique to extract variable information from enormous data, becomes more and more important. Real data often has missing values. Therefore, a method for estimating the missing data is required in application of data mining. Using multiple self-organizing maps (MSOM) proposed by Kikuchi et al. is one of such estimating method. This method does not need a concrete mathematical model and is also available for nonlinear data. However the performance for various missing patterns were unclear, in addition, the comparisons with conventional imputation methods were not provided. This paper demonstrates the performance and the comparison results through simulation experiments with various missing patterns and conventional methods.

本文言語英語
ホスト出版物のタイトル2014 IEEE/SICE International Symposium on System Integration, SII 2014
出版社Institute of Electrical and Electronics Engineers Inc.
ページ796-801
ページ数6
ISBN(電子版)9781479969449
DOI
出版ステータス出版済み - 1 30 2014
イベント7th IEEE/SICE International Symposium on System Integration, SII 2014 - Tokyo, 日本
継続期間: 12 13 201412 15 2014

出版物シリーズ

名前2014 IEEE/SICE International Symposium on System Integration, SII 2014

その他

その他7th IEEE/SICE International Symposium on System Integration, SII 2014
国/地域日本
CityTokyo
Period12/13/1412/15/14

All Science Journal Classification (ASJC) codes

  • 制御およびシステム工学
  • コンピュータ ネットワークおよび通信
  • 情報システム

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