Predicting the Variables That Determine University (Re-)Entrance as a Career Development Using Support Vector Machines with Recursive Feature Elimination: The Case of South Korea

Predicting the Variables That Determine University (Re-)Entrance as a Career Development Using Support Vector Machines with Recursive Feature Elimination: The Case of South Korea

The current study seeks to identify variables that affect the career decision-making of high school graduates with respect to the choice of university (re-)entrance in South Korea where education has great importance as a tool for self-cultivation and social prestige. For pattern recognition, we ado...

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Bibliographic Details
Main Authors: Taejung Park, Chayoung Kim
Format: Article
Language:English
Published: MDPI AG 2020-09-01
Series:Sustainability
Subjects:
SVM-RFE
university (re-)entrance
career decision-making
high-school graduates
ecological systems
Online Access:https://www.mdpi.com/2071-1050/12/18/7365

Internet

https://www.mdpi.com/2071-1050/12/18/7365

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