Abstract
This paper investigates how accurately the prediction of being an introvert vs. extrovert can be made with less than ten predictors. The study is based on a previous data collection of 7161 respondents of a survey on 91 personality and 3 demographic items. The results show that it is possible to effectively reduce the size of this measurement instrument from 94 to 10 features with a performance loss of only 1%, achieving an accuracy of 73.81% on unseen data. Class imbalance correction methods like SMOTE or ADASYN showed considerable improvement on the validation set but only minor performance improvement on the testing set.
Original language | English |
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Title of host publication | 2020 International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 693-696 |
Number of pages | 4 |
ISBN (Electronic) | 9781728149851 |
DOIs | |
Publication status | Published - 2020 Feb |
Event | 2nd International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020 - Fukuoka, Japan Duration: 2020 Feb 19 → 2020 Feb 21 |
Publication series
Name | 2020 International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020 |
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Conference
Conference | 2nd International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020 |
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Country/Territory | Japan |
City | Fukuoka |
Period | 20/2/19 → 20/2/21 |
Bibliographical note
Funding Information:ACKNOWLEDGMENT This research was supported by the Yonsei University Faculty Research Fund of 2019-22-0199.
Publisher Copyright:
© 2020 IEEE.
All Science Journal Classification (ASJC) codes
- Information Systems and Management
- Artificial Intelligence
- Computer Networks and Communications
- Computer Vision and Pattern Recognition
- Information Systems
- Signal Processing