Evaluation of Fuzzy Regression Analysis and Its Application to Oral Age Model

• Toyoura Yoshihiro

  Osaka Institute of Technology

• Kambara Masaki

  Osaka Dental University

• Uemura Mibu

  Osaka Dental University

• Miyake Tatsurou

  Osaka Dental University

• Kawasaki Koji

  Osaka Dental University

• Watada Junzo

  Osaka Institute of Technology

抄録

Fuzzy multivariate analyses including linear regression analysis, fuzzy time-series analysis, fuzzy possibilistic linear model, etc. are formulated in terms of the extension principle. One objective of a fuzzy linear regression model is to build a model using fuzzy numbers which represent the possibilities included in the system. Therefore, the fuzzy regression model is also named a possibilistic regression model. Hitherto, it is hard for us to measure the goodness of a fuzzy regession model. As there is no index to evaluate the fuzzy regression model, it is not easy to evaluate the possibility of a fuzzy regression model. In this paper, we propose two indices to evaluate a fuzzy regression model. Our indices make us understand ike distribution of data and explain the relation of the distribution of data with the possibilistic interval of a fuzzy regression model The paper also exemplifies the characteristics of an Evaluation Index and builds an oral age model on ike basis of real data about the age and the number of sound teeth.

収録刊行物

• International Journal of Biomedical Soft Computing and Human Sciences: the official journal of the Biomedical Fuzzy Systems Association

  International Journal of Biomedical Soft Computing and Human Sciences: the official journal of the Biomedical Fuzzy Systems Association 6 (1), 41-49, 2000

  バイオメディカル・ファジィ・システム学会

キーワード

• Evaluation Index
• Fuzzy Regression Analysis
• Linear Programming Problem
• Oral Age Model

詳細情報

• CRID: 1390001206080552832
• NII論文ID: 110003945939
• DOI: 10.24466/ijbschs.6.1_41
• ISSN: 2424256X
• ISSN: 21852421
• 本文言語コード: en
• データソース種別:
  • JaLC
  • CiNii Articles
• 抄録ライセンスフラグ: 使用不可