Are You an Introvert or Extrovert? Accurate Classification with only Ten Predictors

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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 languageEnglish
Title of host publication2020 International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages693-696
Number of pages4
ISBN (Electronic)9781728149851
DOIs
Publication statusPublished - 2020 Feb
Event2nd International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020 - Fukuoka, Japan
Duration: 2020 Feb 192020 Feb 21

Publication series

Name2020 International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020

Conference

Conference2nd International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020
Country/TerritoryJapan
CityFukuoka
Period20/2/1920/2/21

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

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