The Mental Health Fitness Tracker project focuses on analyzing and predicting mental fitness levels of individuals from various countries with different mental disorders. It utilizes regression techniques to provide insights into mental health and make predictions based on the available data.
Here're some of the project's best features:
- Multimodal Regression Analysis
- Data Preprocessing and Cleaning
- Visualization for Interpretability
- Model Performance Ranking
1. Ensure Jupyter is Installed:
pip install jupyter
2. Open Jupyter Notebook:
jupyter notebook
3. Access the Notebook:
Your default web browser will open showing the Jupyter Notebook interface.
Navigate to the directory where the .ipynb file is located and click on the file to open it.
4. Run the Notebook:
Inside the Jupyter Notebook interface you can run the code cells one by one or all at once.
To run a cell select it and press Shift + Enter.
5. Review the Results:
The notebook will execute the code cells training regression models generating visualizations and printing performance metrics.
Review the output and visualizations to understand the precision and performance of each regression model.
6. Interpret the Results:
Look for the summary section and model ranking to understand which regression models performed the best and the least.
7. Save Changes:
If you make any changes or add comments remember to save the notebook after running the code
Technologies used in the project:
- Python
- Jupyter Notebook
- Scikit-Learn
- Matplotlib
- Seaborn
This project is licensed under the MIT License