Accuracy of data analysis on university student's major subject and job sector prediction using KNN and decision tree algorithm

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Abstract

The students are at a loss when it comes to choosing their major or field of work due to inefficient school system and decision making of the parents. This problem can be resolved to some extent by using classifiers. The accuracy of the decision the students will take can be gauged these using classifiers. These classifiers such as KNeighbor classifier and Decision tree classifier help to gauge the accuracy of the prediction. Decision tree classifier is more accurate in predicting the correct outcome. This use of classifier will help the students to take the right decision in case of their study and career field. Based on a student’s extra-curricular activity, Olympiad and HSC grade it predicts the major subject of an undergraduate student. Again, based on an undergraduate student’s major subject, CGPA and extra-curricular activity it predicts job of the student.

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Description

Cataloged from PDF version of thesis.
Includes bibliographical references (pages 31-32).
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021.

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Thesis