https://github.com/prernarohra/mental-health-prediction

This project focuses on predicting mental health outcomes using machine learning algorithms. By analyzing various psychological, social, and lifestyle factors, the model aims to identify individuals at risk, enabling early intervention and support.
https://github.com/prernarohra/mental-health-prediction

data-analysis data-science data-visualization machine-learning mental-health python

Last synced: 4 days ago
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This project focuses on predicting mental health outcomes using machine learning algorithms. By analyzing various psychological, social, and lifestyle factors, the model aims to identify individuals at risk, enabling early intervention and support.

• Host: GitHub
• URL: https://github.com/prernarohra/mental-health-prediction
• Owner: prernarohra
• License: mit
• Created: 2024-08-26T12:03:45.000Z (5 months ago)
• Default Branch: main
• Last Pushed: 2024-09-17T17:25:49.000Z (4 months ago)
• Last Synced: 2024-11-22T17:18:03.561Z (2 months ago)
• Topics: data-analysis, data-science, data-visualization, machine-learning, mental-health, python
• Language: Jupyter Notebook
• Homepage:
• Size: 6.18 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# :brain: Mental Health Prediction

## :clipboard: Overview

The Mental Health Prediction project is a data science and machine learning attempt that aims to predict mental health treatment based on a variety of factors. This project uses classification algorithms to examine and predict the possibility of mental health therapy, such as whether or not to see a physiatrist based on a dataset containing a variety of psychological and demographic characteristics.

## :sparkles: Features

1. Data Analysis: Comprehensive analysis of mental health dataset.

2. Visualization: Graphical representation of data insights.

3. Predictive Modeling: Used machine learning algorithms to predict mental health treatment.

4. Prediction Result: Generated results by inputing required parameters.

## :bar_chart: Dataset

The dataset used in this project contains several features related to mental health treatment including Gender, family history, stress, mood swings, days indoor etc.

The dataset is split into training and testing sets to evaluate model performance.

## :rocket: Usage

Enter the parameters in the last cell and then run the project, it will show the prediction according to the input parameters.

## 🤝 Contributing

If you would like to contribute to this project, please fork the repository and submit a pull request. Ensure that your changes are well-documented and tested.