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Performed univariate and bivariate analysis to understand the features and their relationships for loan approval prediction. Achieved highest accuracy of 98% for Extreme Gradient Boosting among all tested machine learning classification models.

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SK7here/Loan-Approval-Prediction

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LOAN APPROVAL PREDICTION

ML Algorithms used:

 1.Logistic Regression
 2.Decision Trees
 3.Random Forest
 4.Extreme gradient boosting
(Stratified k-folds cross Validation is used while validating each model to ensure genericness of model)

Data Analysis techniques used:

 1.Univariate Analysis
 2.Bivariate Analysis

Data visualization techniques used:

 1.Bar plot
 2.Stacked Bar plot
 3.Distribution plot
 4.Box plot
 5.Heat Map


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Performed univariate and bivariate analysis to understand the features and their relationships for loan approval prediction. Achieved highest accuracy of 98% for Extreme Gradient Boosting among all tested machine learning classification models.

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