🧠 Neuro Gambling Scanner - Flask API

This repository contains a Flask-based REST API for predicting gambling risk levels using a pre-trained Support Vector Machine (SVM) model. It is part of the Neuro Gambling Scanner project, aimed at identifying potential gambling addiction risks based on user data.

🚀 Features

• Accepts .xlsx (Excel) files with 11,680 features per record.
• Predicts risk category using a trained SVM model.
• Returns predictions in JSON format.
• Cross-Origin Resource Sharing (CORS) enabled for easy integration with front-end/mobile apps.
• Deployable via railway.com for production environments.

🗂️ Repository Structure

├── app.py # Main Flask application code

├── svm_model.pkl # Trained SVM model (11680 input features)

├── requirements.txt # Required Python packages

├── README.md

📡 API Endpoints

✅ GET /

Returns a welcome message.

Response: "Welcome to the SVM Model Prediction API!"

🔍 POST /predict

Uploads an Excel file for prediction.

🔸 Request: Content-Type: multipart/form-data Field name: file Format: .xlsx Excel file with 11680 columns

🧠 About the Model

Model Type: Support Vector Machine (SVM) Input Features: 11680 (possibly fMRI behavioral signals) Output: Risk Category →

0 (Low),

1 (Medium),

2 (High)

Trained using Scikit-learn

Author

This repository was created and maintained by Muhammad Zain Mushtaq