Student Employability Analysis using Machine Learning and Data Visualization

Author(s)	Abhay Ramamurthy, Karthik Chandramouli
Country	India
Abstract	This study presents a random forest algorithm student prioritization tool employing ensemble decision trees for classification and incorporating weights of prioritization with predefined criteria. The tool enhances speed in the selection process through candidate classification thereby enhancing efficiency and precision in the identification of suitable candidates who possess attributes most consistent with those desired by the institution. Demonstrating its advantage over traditional methods is in this way.
Keywords	Machine learning,shortlisting
Field	Engineering
Published In	Volume 6, Issue 3, May-June 2024
Published On	2024-06-02
Cite This	Student Employability Analysis using Machine Learning and Data Visualization - Abhay Ramamurthy, Karthik Chandramouli - IJFMR Volume 6, Issue 3, May-June 2024. DOI 10.36948/ijfmr.2024.v06i03.20575
DOI	https://doi.org/10.36948/ijfmr.2024.v06i03.20575
Short DOI	https://doi.org/gtxrsh

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International Journal For Multidisciplinary Research