How to Use the Lotto 6/42 Predictive Analytics System
Getting Started
Welcome to the Lotto 6/42 Predictive Analytics System! This educational tool demonstrates machine learning techniques applied to lottery data analysis. Important: Lottery outcomes are inherently random and cannot be predicted with certainty.
Key Features
- Prediction Generation: Generate probabilistic predictions using trained ML models
- Data Management: View, add, edit, and delete historical lotto draw data
- Real-time Analysis: Predictions based on the latest available data
- Educational Focus: Learn about data science and ML techniques
Generating Predictions
- Click the "Generate Prediction" button on the home page
- Wait for the system to process the latest historical data
- Review your prediction results, including:
- 6 predicted numbers with probability scores
- Confidence level of the prediction
- Alternative picks for additional options
Managing Data
To keep predictions accurate, maintain up-to-date historical data:
- View Data: Click "Manage Data" to see all historical draws
- Add Data: Add new draw results with date and 6 unique numbers (1-42)
- Edit Data: Modify existing draw information
- Delete Data: Remove incorrect or duplicate entries
Understanding Results
- Predicted Numbers: The 6 numbers most likely to appear next
- Confidence Score: Average probability (higher = stronger prediction)
- Alternative Picks: Next best numbers if you want more options
- Probability Chart: Visual representation of prediction certainty
Theme Toggle
Use the theme switch in the top-right corner to toggle between light and dark modes for better viewing comfort.
Important Notes
- This system provides educational insights only
- Predictions are based on historical patterns, not guaranteed outcomes
- Typical accuracy is around 14-16% (slightly better than random)
- Play responsibly and only spend what you can afford to lose
Troubleshooting
- Slow Performance: Large datasets may take time to process
- Errors: Check data format and ensure numbers are valid (1-42, unique)
- Model Issues: Verify model files exist in the models/ directory
For more detailed information, refer to the USER_MANUAL.md file included with the project.