Multiclass probabilistic classification for support vector machines

Ji Sang Bae; Jong-Ok Kim

doi:10.1587/transinf.2014EDL8167

Multiclass probabilistic classification for support vector machines

Ji Sang Bae, Jong-Ok Kim

School of Electrical Engineering

Research output: Contribution to journal › Article › peer-review

2 Citations (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 language	English
Pages (from-to)	1251-1255
Number of pages	5
Journal	IEICE Transactions on Information and Systems
Volume	E98D
Issue number	6
DOIs	https://doi.org/10.1587/transinf.2014EDL8167
Publication status	Published - 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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10.1587/transinf.2014EDL8167

Cite this

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Multiclass probabilistic classification for support vector machines

Abstract

Keywords

ASJC Scopus subject areas

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