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In this project, based on the historical data of customers, who has applied for loans, we will identify whether loan should be approved or not. This dataset belongs to Lending Club.

License: Apache License 2.0

Jupyter Notebook 80.31% Shell 0.39% Python 19.30%
jupyter-notebook lendingclub loan-applications loan-default-prediction python randomforestclassifier xgboost-classifier

loan_approval's Introduction

Loan_approval

In this project, based on the historical data of customers, who has applied for loans, we will identify whether loan should be approved or not.

1. Analysis :- Feature Selection (Dimension Reduction)

1.1 Plotting Correlation

Correlation

1.2 Variance Check

1.3 Missing Values Check

2. Model Building

2.1 Logistic Regression 2.2 Random Forest 2.3 Xgboost Classifier

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