This project implements a financial transaction anomaly detection system using a Flask backend for simulating a data stream and anomaly detection, and a React frontend for visualizing the data stream and highlighting the anomalies.

Backend: Flask API that simulates a financial transactional data stream and detects anomalies using Z-Score and Isolation Forest methods. Frontend: React app that visualizes the data stream with anomalies highlighted on a graph.

• Prerequisites
• Installation
• Backend Setup
• Frontend Setup
• Running the Application
• Project Structure
• Technologies Used

Before you begin, ensure you have the following installed:

• Python 3.8+
• Node.js 14+
• npm 6+

Clone the repository and navigate to root directory:

git clone https://github.com/edwinmvk/anomaly-detection.git
cd anomaly-detection

1. Navigate to the backend directory from root:

   cd backend

2. Install the required Python packages:

   pip install -r requirements.txt

1. Navigate to the frontend directory from root:

   cd frontend

2. Install the required npm packages:

   npm install

1. Start the Flask backend:

   • In a new terminal, navigate to the backend directory:

     cd backend
     python server.py

     The backend will start running on http://localhost:5000.

2. Start the React frontend:

   • In a new terminal, navigate to the frontend directory:

     cd frontend
     npm start

     The frontend will start running on http://localhost:3000.

3. Open your web browser and go to http://localhost:3000 to view the application.

anomaly-detection/
│
├── backend/
│   ├── server.py         # Flask backend
│   └── requirements.txt  # Python dependencies
│
└── frontend/
    ├── package.json      # npm dependencies and scripts
    ├── public/
    └── src/
        ├── App.js        # Main React component
        └── ...           # Other React components and assets

• Backend:
  • Flask
  • NumPy
  • SciPy
  • scikit-learn
• Frontend:
  • React
  • Chart.js
  • react-chartjs-2

For more details, please refer to the requirements.txt and package.json files.