sup25/Laon-eligiblity-prediction-React-python-flask-

Loan eligibility prediction using logistic regression

Loan eligibility prediction using logistic regression is a statistical method that predicts whether a borrower will be approved or denied for a loan based on their financial and personal information.
Logistic regression is a type of binary classification algorithm that can model the probability of the binary outcome (approved or denied) based on a set of predictor variables.
The model is trained and tested on a historical dataset of loan applications, and once trained and tested, it can be used to predict the likelihood of loan approval for new loan applications.
Logistic regression is effective for loan eligibility prediction because it can handle both categorical and continuous predictor variables, and it can provide insights into the factors that influence loan approval decisions.

Authors

• @Suparna Adhikari

• @Ranjan Bhattrai

• @Heena viadya

Folder

Client: React

Others: Python

Run Locally

Clone the project

  git clone https://github.com/sup25/Laon-eligiblity-prediction-React-python-flask-.git

Go to the project directory (FrontEnd)

  cd client

Install dependencies

  npm install

Start the server

  npm run start

For BackEnd

  venv/Scripts/activate

  python main.py

If you want to run specific file

  python <filename>.py

Screenshots