Processing loan applications using Machine Learning

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  • Compared the performance of 5 different ML classifiers : logistic regression, decision tree, support vector machine, k-Nearest Neighbors (kNN) and gaussian naiver bayes, for predicting whether a loan application must be approved or not.
  • The use of effective data-preprocessing techniques for dealing with missing values and removing non-essential features ensured that these models outperformed prior work done in this field.
  • Decision tree model gave perfect accuracy of 100% and was suggested to be the best classifier for this application.