TY - JOUR
T1 - Comparison between Fisher's Ratio and Information Gain with SVM classifier for 3 levels of enthusiasm classification through face recognition
AU - Rustam, Z.
AU - Kristina, Andrea Laksmirani
AU - Satria, Y.
N1 - Funding Information:
This research was supported financially by the University of Indonesia, with a DRPM PITTA 2017 research grant scheme.
Publisher Copyright:
© Published under licence by IOP Publishing Ltd.
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2021/2/15
Y1 - 2021/2/15
N2 - The enthusiasm level of a person is an important measurement in real-world problems. This paper, therefore, presents face recognition classification for enthusiasm level, based on supervised machine learning, using Support Vector Machine (SVM) as a classifier, with a one-vs-one method because the data consists of more than two classes. In addition, Fisher's Ratio and Information Gain are applied in the selection of contributive features, and the goals were to present an accuracy comparison between SVM and Fisher's Ratio, as wells as with Information Gain, and the results showed the accuracy at 88,89%, and 80,95238%, respectively. This indicates the combination of SVM with Fisher Ratio to be better.
AB - The enthusiasm level of a person is an important measurement in real-world problems. This paper, therefore, presents face recognition classification for enthusiasm level, based on supervised machine learning, using Support Vector Machine (SVM) as a classifier, with a one-vs-one method because the data consists of more than two classes. In addition, Fisher's Ratio and Information Gain are applied in the selection of contributive features, and the goals were to present an accuracy comparison between SVM and Fisher's Ratio, as wells as with Information Gain, and the results showed the accuracy at 88,89%, and 80,95238%, respectively. This indicates the combination of SVM with Fisher Ratio to be better.
KW - Fisher's ratio
KW - recognition
KW - SVM classifier
UR - http://www.scopus.com/inward/record.url?scp=85101746053&partnerID=8YFLogxK
U2 - 10.1088/1742-6596/1752/1/012042
DO - 10.1088/1742-6596/1752/1/012042
M3 - Conference article
AN - SCOPUS:85101746053
SN - 1742-6588
VL - 1752
JO - Journal of Physics: Conference Series
JF - Journal of Physics: Conference Series
IS - 1
M1 - 012042
T2 - 3rd International Conference on Statistics, Mathematics, Teaching, and Research 2019, ICSMTR 2019
Y2 - 9 October 2019 through 10 October 2019
ER -