Education Loan Prediction Analysis


Authors : Sanskruti Naik; Ganesh Manerkar

Volume/Issue : Volume 7 - 2022, Issue 4 - April

Google Scholar : https://bit.ly/3IIfn9N

Scribd : https://bit.ly/3khDqCt

DOI : https://doi.org/10.5281/zenodo.6496523

Education loans help students to cover the cost of tuition, books and supplies, and living expenses while in the process of pursuing a degree. Education loans are granted by private banks and by government organizations. This paper isan analysis on student loan data for the interest free education loans granted to students as per the standards and rules of Goa Education Development Corporation(GEDC). The dataset is prepared complying the standards of criteria mentionedby organization. The accuracy of prediction is compared using models like Support Vector Machine(SVM), Random forest(RF), Logistic regression(LR), Decision tree classifier and XG-boost.

Keywords : Loan, Prediction, Support Vector Machine, RanDom Forest, Logistic Regression, Decision Tree Classifier, XG- Boost.

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