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Loan Approval Classification

This project aims to classify loan applications as approved or rejected using various machine learning models. The dataset used in this project contains information about loan applicants, such as their income, credit score, and loan amount.

Getting Started

Prerequisites

  • Python 3.x
  • Virtual environment (optional but recommended)

Installation

  1. Clone the repository:

    git clone <repository-url>
    cd <repository-directory>
  2. Create and activate a virtual environment:

    python -m venv venv
    source venv/bin/activate  # On Windows use `venv\Scripts\activate`
  3. Install the required packages:

    pip install -r requirements.txt

Dataset

Download the dataset from this link and place the CSV files in the data/ directory with the name as LoanApproval_Raw.csv.

Running the Project

  1. Exploration:

    python src/01_exploration.py
  2. Cleaning:

    python src/02_cleaning.py
  3. Processing:

    python src/03_processing.py
  4. Training:

    python src/04_training.py
  5. PyCaret Implementation: This is an alternative to the above steps. It uses PyCaret to automate the entire process.

    python src/pycaret_pipeline.py

License

This project is licensed under the MIT License.

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Classifies loan applications using machine learning

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