Abstract
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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
