A pupil data based classification model for education learning states
- 주제(키워드) classification model , k-fold cross validation , machine learning , pupil , Support Vector Machine
- 후원정보 Ministry of Education
- 등재 SCOPUS
- 발행기관 Institute of Electrical and Electronics Engineers Inc.
- 발행년도 2017
- URI http://www.dcollection.net/handler/ewha/000000156433
- ISBN 9781509040315
- 본문언어 영어
- Published As http://dx.doi.org/10.1109/ICTC.2017.8190960
초록/요약
In this paper, we propose a classification model for learning state based on individual biometric data. In particular, we use the pupil size as a biometric data and the data has been collected from 72 participants. We also deploy the support vector machine (SVM) in conjunction with k-fold validation as an analysis tool. In order to improve the performance of the SVM, the we remove outliers from the data set and normalize it. Our experiment results show that the accuracy of the proposed classification model is up to 68.8% and thus confirm the effectiveness of the proposed classification model using the pupil data. © 2017 IEEE.
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