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Applying various machine learning classification models to predict the credit quality of new loan applicants (KNN, Logistic regression, Naïve Bayes, Decision Trees, Random Forest, Neural Networks, SVM, Linear, and Quadratic Discriminant Analysis)

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CONSUMER_LOAN_DEFAULT_PREDICTION

A project for the Projects in Data Analytics for Decision Making course, the Spring 2022 semester.

Applying various machine learning classification models to predict the credit quality of new loan applicants (KNN, Logistic regression, Naïve Bayes, Decision Trees, Random Forest, Neural Networks, SVM, Linear, and Quadratic Discriminant Analysis) using R language

Full report: https://rpubs.com/Manunpat/948446

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Applying various machine learning classification models to predict the credit quality of new loan applicants (KNN, Logistic regression, Naïve Bayes, Decision Trees, Random Forest, Neural Networks, SVM, Linear, and Quadratic Discriminant Analysis)

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