Obesity Risk Prediction CNN Model

This repository hosts a Convolutional Neural Network (CNN) model that predicts the risk of obesity in individuals with an impressive accuracy of 87.01%. Developed on Google Colab, this model harnesses the platform's powerful GPUs and collaborative environment.

Model Overview

• Objective: Accurately predict obesity risk from input data.
• Accuracy: Attained 87.01% on the test dataset.
• Dataset: Sourced from a Kaggle competition via its API.
• Frameworks: Built with TensorFlow/Keras.
• Training Environment: Google Colab.

Features

• Input: Accepts data with shape (22, 1), including normalization and dropout layers.
• Output: Outputs the probability of obesity risk.
• Architecture: Consists of 5 layers, featuring convolutional layers, dropout layers, batch normalization, and fully connected layers.
• Optimization: Utilizes the Adam optimizer with a learning rate of 0.00005.

Results

In a sample test of 10, the model correctly predicted 8 instances, indicating potential areas for improvement to enhance accuracy.

Your contributions and feedback are invaluable as we continue to refine this model. Feel free to clone and explore its capabilities!