Multiclass probabilistic classification for support vector machines

Ji Sang Bae, Jong-Ok Kim

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Support Vector Machine (SVM) is one of the most widely used classifiers to categorize observations. This classifier deterministically selects a class that has the largest score for a classification output. In this letter, we propose a multiclass probabilistic classification method that reflects the degree of confidence. We apply the proposed method to age group classification and verify the performance.

Original languageEnglish
Pages (from-to)1251-1255
Number of pages5
JournalIEICE Transactions on Information and Systems
VolumeE98D
Issue number6
DOIs
Publication statusPublished - 2015 Jun 1

Keywords

  • Age-group classification
  • Multiclass classification
  • Probabilistic classification
  • SVM

ASJC Scopus subject areas

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

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