Impute-VSS: A Comprehensive Web-Based Visualization and Simulation Suite for Comparative Data Imputation and Statistical Evaluation

Overview

Impute-VSS is a web-based solution engineered to address the intricate challenges of data imputation. This tool offers a unified interface combining multiple imputation techniques, including traditional statistical methods and machine learning–based algorithms, along with modular pipeline capabilities. Designed for both researchers and practitioners, Impute-VSS enables analytical exploration of missing data, comparative assessments of imputation methods, and detailed visual diagnostics to support data-driven decision-making.

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Features

1. Comprehensive Imputation Techniques:

   • Complete Case Analysis (CCA): Analyze datasets by excluding incomplete records.
   • Univariate Imputation: Employ statistical techniques like Mean, Mode, Median, Constant Value, and Random Sample Imputation for simplicity and speed.
   • Multivariate Imputation: Integrate advanced methods such as K-Nearest Neighbors (KNN) and Multiple Imputation by Chained Equations (MICE) for datasets with complex interdependencies.
   • Machine Learning–Based Imputation: Utilize algorithms like Gradient Boosting, Random Forest Regressor, and Support Vector Regression to predict missing values based on the overall dataset context.

2. Real-time Visual Feedback:

   • Interactive Charts: Heatmaps, KDE Plots, Histograms, Correlation Matrices, and Box Plots to dynamically visualize imputation outcomes.
   • Comparative Analysis: Instant updates showcasing differences across techniques and their statistical significance.

3. Imputation Pipeline Management:

   • Create modular workflows and export them in the proprietary .impvss format for consistent replication and sharing.
   • Ensure efficient reuse of imputation strategies without compromising dataset privacy.

4. Cross-Platform Compatibility:

   • Fully web-based, compatible with desktops, tablets, and mobile devices for seamless accessibility across platforms.

5. Statistical Metrics and Comparisons:

   • Evaluate methods based on Kernel Density Estimation (KDE) overlap, Skewness, Kurtosis, Kolmogorov-Smirnov Statistic, and Kullback-Leibler Divergence for robust statistical insights.

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Installation

1. Clone the Repository:

   git clone https://github.com/vartul-shrivastava/Impute-VSS-26022025.git
   cd Impute-VSS-26022025

2. Install Dependencies: Ensure you have Python 3.12.3 or above installed. Then run:

      pip install -r requirements.txt

3. Run the Application: Start the Flask application by executing:

      python app.py

4. Access Impute-VSS Dashboard: Open your web browser and navigate to http://127.0.0.1:5000 (or the specified port) to view the Impute-VSS dashboard.

Packages Requirements

Kindly install these packages through requirements.txt to run the Impute-VSS application. These packages support functionalities such as web serving, numerical computations, data manipulation, machine learning, and system monitoring.

1. Flask
2. pandas
3. numpy
4. scikit-learn
5. scipy
6. beautifulsoup4
7. psutil

Troubleshooting

• Installation Issues:

  • Error during pip install -r requirements.txt:
    • Solution: Ensure you are using Python 3.12.3 or above. Upgrade pip using pip install --upgrade pip and retry installation. Also, verify your network or proxy settings if package downloads fail.

• Port Conflicts:

  • Flask fails to start due to a port conflict:
    • Solution: Modify the default port in app.py by changing app.run() to app.run(port=5001) (or another available port). Ensure no other process is using the specified port.

• Module Import Errors:

  • Encountering ModuleNotFoundError or ImportError:
    • Solution: Confirm all dependencies are installed correctly. Re-check the requirements.txt for any missing packages and install them manually if necessary.

• Browser Rendering Issues:

  • Dashboard not displaying correctly or missing visual elements:
    • Solution: Clear your browser cache, try using another browser (such as Chrome, Firefox, or Edge), and ensure that JavaScript is enabled in your browser settings.

• General Debugging:

  • Review the terminal or console for error messages when running the application.
  • Verify that the file structure is complete and that all required files (CSS, JavaScript, HTML templates) are in their correct directories.
  • Restart the application after making any configuration or source file modifications.

File Structure

├── static/
│   ├── css/          # Stylesheet
│   ├── images/       # Backgrounds and logos
│   ├── js/           # JavaScript file
├── templates/        # HTML template
├── app.py            # Flask application
├── requirements.txt  # Dependencies
├── README.md         # Documentation

Support

• Author Emails:
  • Vartul Shrivastava: [email protected]
  • Prof. Shekhar Shukla: [email protected]

License

Impute-VSS is licensed under the MIT License. See the LICENSE file for more details.