Future Insight Predictor
This Streamlit application helps you predict future values based on historical data in a CSV file. It offers various machine learning algorithms to choose from and provides informative visualizations to assess model performance.
Getting Started
- Prerequisites:
- Python 3.x
- Streamlit:
pip install streamlit
- Pandas:
pip install pandas
- scikit-learn:
pip install scikit-learn
- matplotlib:
pip install matplotlib
- seaborn:
pip install seaborn
- Run the app:
- Save the code as
app.py.
- Open a terminal, navigate to the directory containing the file, and run:
How it Works
- Upload a CSV file containing your historical data.
- The app will display a preview of the data.
- Preprocessing is applied to format the data for modeling.
- Select the features (independent variables) and target variable (dependent variable) for prediction.
- Choose a prediction task based on your data domain (e.g., Stock Sale, Real Estate Prices).
- Select a machine learning algorithm for prediction.
- Click "Train and Evaluate" to train the model and view the results.
Output
- The predicted value for the next month.
- Model accuracy score and cross-validation scores for evaluation.
- Visualization comparing actual vs predicted values, highlighting overestimations and underestimations.
Note
This is a basic implementation and can be further enhanced with additional features and functionalities based on your specific needs.
Contributing
Feel free to fork the repository and submit pull requests with improvements or additional features!
