Fuzzy decision-making SVM with an offset for real-world lopsided data classification

Boyang Li, Takayuki Furuzuki, Kotaro Hirasawa

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

An improved support vector machine (SVM) classifier model for classifying the real-world lopsided data is proposed. The most obvious differences between the model proposed and conventional SVM classifiers are the designs of decision-making functions and the introduction of an offset parameter. With considering about the vagueness of the real-world data sets, a fuzzy decision-making function is designed to take the place of the traditional sign function in the prediction part of SVM classifier. Because of the existence of the interaction and noises influence around the boundary between different clusters, this flexible design of decision-making model which is more similar to the real-world situations can present better performances. In addition, in this paper we mainly discuss an offset parameter introduced to modify the boundary excursion caused by the imbalance of the real-world datasets. Because noises in the real-world can also influence the separation boundary, a weighted harmonic mean (WHM) method is used to modify the offset parameter. Due to these improvements, more robust performances are presented in our simulations.

Original languageEnglish
Title of host publication2006 SICE-ICASE International Joint Conference
Pages143-148
Number of pages6
DOIs
Publication statusPublished - 2006
Event2006 SICE-ICASE International Joint Conference - Busan
Duration: 2006 Oct 182006 Oct 21

Other

Other2006 SICE-ICASE International Joint Conference
CityBusan
Period06/10/1806/10/21

Fingerprint

Support vector machines
Classifiers
Decision making

Keywords

  • Classification
  • Fuzzy decision-making function
  • Real-world lopsided dataset
  • SVM
  • WHM offset

ASJC Scopus subject areas

  • Computer Science Applications
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Cite this

Li, B., Furuzuki, T., & Hirasawa, K. (2006). Fuzzy decision-making SVM with an offset for real-world lopsided data classification. In 2006 SICE-ICASE International Joint Conference (pp. 143-148). [4108812] https://doi.org/10.1109/SICE.2006.315389

Fuzzy decision-making SVM with an offset for real-world lopsided data classification. / Li, Boyang; Furuzuki, Takayuki; Hirasawa, Kotaro.

2006 SICE-ICASE International Joint Conference. 2006. p. 143-148 4108812.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Li, B, Furuzuki, T & Hirasawa, K 2006, Fuzzy decision-making SVM with an offset for real-world lopsided data classification. in 2006 SICE-ICASE International Joint Conference., 4108812, pp. 143-148, 2006 SICE-ICASE International Joint Conference, Busan, 06/10/18. https://doi.org/10.1109/SICE.2006.315389
Li B, Furuzuki T, Hirasawa K. Fuzzy decision-making SVM with an offset for real-world lopsided data classification. In 2006 SICE-ICASE International Joint Conference. 2006. p. 143-148. 4108812 https://doi.org/10.1109/SICE.2006.315389
Li, Boyang ; Furuzuki, Takayuki ; Hirasawa, Kotaro. / Fuzzy decision-making SVM with an offset for real-world lopsided data classification. 2006 SICE-ICASE International Joint Conference. 2006. pp. 143-148
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