AyushTyagi1610/Credit-Risk-Modelling

Built a model to determine the risk associated with extending credit to a borrower. Performed Univariate and Bivariate exploration using various methods such as pair-plot and heatmap to detect outliers and to monitor the behaviour and correlation of the features. Imputed the missing values using KNN Imputer and implemented SMOTE to address the imbalanced data. Trained the model using KNN, Decision Trees, Logistic Regression and Random Forest to achieve the best accuracy of 93%.

Jupyter Notebook