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A classification problem that Predicts whether a client should be approved for a loan based on their credentials, income, and previous credit history about them.

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sanskar7447/Loan-Approval-Prediction-

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Loan-Approval-Prediction-

A classification problem that Predicts whether a client should be approved for a loan based on their credentials, income, and previous credit history about them.

This project covers the whole process from problem statement to model development and evaluation and finally prediction on test data:

1-Exploratory Data Analysis (EDA)
2-Data Pre-processing
3-Model Development and Evaluation
4-Predection

Problem Statement-

This is a classification problem where we have to predict whether a loan will be approved or not. Specifically, it is a binary classification problem where we have to predict either one of the two classes given i.e. approved (Y) or not approved (N).The dependent variable or target variable is the Loan_Status, while the rest are independent variable or features. We need to develop a model using the features to predict the target variable.

I scored accuracy of about 80.80% using RandomForestClassifier. I believe this is a nice score to begin with.

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A classification problem that Predicts whether a client should be approved for a loan based on their credentials, income, and previous credit history about them.

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