Loan Approval Prediction Using Machine Learning Github
Accuracy with logistic regression and decision tree was 75 whereas using knn the accuracy came out to be 63.
Loan approval prediction using machine learning github. In this blog post i d be walking us through loan prediction using some selected machine learning algorithms. If nothing happens download github desktop and try again. Use git or checkout with svn using the web url.
If the loan amount is less the chances of loan approval should be high. Predicting loan approval using machine learning. If nothing happens download xcode and try again.
For more details you can visit the official post. A classification problem which predicts if a loan will get approved or not. Based on different parameters a machine learning model to predict whether a person is eligible for loan or not trained model using three classifiers.
Specifically it is a binary classification problem where we have to predict either one of the two classes given i e. Our aim from the project is to make use of pandas matplotlib seaborn libraries from python to extract insights from the data and xgboost scikit learn libraries for machine learning. If nothing happens download github desktop and try again.
Lesser the amount to be paid monthly to repay the loan the higher the chances of loan approval. Provided by analytics vidhya the loan prediction task is to dicide whether we should approve the loan request according to their status. Contribute to aaryan 2310 loan prediction flask development by creating an account on github.
This is a classification problem where we have to predict whether a loan will be approved or not. Approved y or not approved n. The dataset for this project is retrieved from github the home of.
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