<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>This study analyzes the career development direction of college students through logistic regression and gray theory to provide more accurate career planning guidance for college students. Logistic regression classification algorithm and gray theory are used to study career influencing factors and predict future career development trends. The significant influence of academic performance, English proficiency, and civic and political cultivation on career direction is identified by analyzing the sample data of S college students. The model’s accuracy is significantly higher than random guessing, up to 79.8%. The results show that the combination of logistic regression and gray theory can effectively predict the career direction of college students, provide data-supported career guidance services for colleges and universities, and help students make more reasonable career planning.</p>
</abstract>

This study analyzes the career development direction of college students through logistic regression and gray theory to provide more accurate career planning guidance for college students. Logistic regression classification algorithm and gray theory are used to study career influencing factors and predict future career development trends. The significant influence of academic performance, English proficiency, and civic and political cultivation on career direction is identified by analyzing the sample data of S college students. The model’s accuracy is significantly higher than random guessing, up to 79.8%. The results show that the combination of logistic regression and gray theory can effectively predict the career direction of college students, provide data-supported career guidance services for colleges and universities, and help students make more reasonable career planning.

Research on the precise pointing of college students’ career based on logistic regression classification algorithm

Harbin University of Science and Technology

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

This study analyzes the career development direction of college students through logistic regression and gray theory to provide more accurate career planning...

Research on the precise pointing of college students’ career based on logistic regression classification algorithm

Online veröffentlicht: 26. Feb. 2024

Seitenbereich: -

Eingereicht: 10. Jan. 2024

Akzeptiert: 17. Jan. 2024

DOI: https://doi.org/10.2478/amns-2024-0514

Schlüsselwörter
Logistic regression classification algorithm, Gray theory, Career development, Influence factor

© 2024 Lin Xu et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Research on the precise pointing of college students’ career based on logistic regression classification algorithm

Online veröffentlicht: 26. Feb. 2024

Seitenbereich: -

Eingereicht: 10. Jan. 2024

Akzeptiert: 17. Jan. 2024

DOI: https://doi.org/10.2478/amns-2024-0514

SchlüsselwörterLogistic regression classification algorithm, Gray theory, Career development, Influence factor

© 2024 Lin Xu et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
Logistic regression classification algorithm, Gray theory, Career development, Influence factor