ML-Model-Evaluation-Dashboard-Scripted

A modular and easy-to-use machine learning model evaluation tool with both Streamlit UI and command-line interface (CLI) support. The goal is to allow fast and flexible experimentation on tabular datasets for classification tasks — especially to understand how feature selection (including PCA) impacts model performance.

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🚀 Features

• Upload any tabular CSV dataset

• Select target column and drop irrelevant columns

• Automatically apply PCA if high dimensionality is detected

• Perform feature selection:

  • Elbow method (auto)
  • Manual top-N features

• Evaluate using Logistic Regression

• Get precision, recall, F1-score, and support metrics

• Works both via:

  • 📊 Streamlit UI
  • 🔧 Command-line script

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💻 Streamlit UI: How to Run

▶️ Steps:

1. Clone this repo

   git clone https://github.com/RohitXJ/ML-Model-Evaluation-Dashboard-Scripted.git
   cd ML-Model-Evaluation-Dashboard-Scripted

2. Create a virtual environment (recommended)

   python -m venv venv
   source venv/bin/activate   # On Windows: venv\Scripts\activate

3. Install required packages

   pip install -r requirements.txt

4. Run the Streamlit app

   cd streamlit_app_version
   streamlit run streamlit_app.py

🧪 Then:

• Upload your CSV file.
• Choose the target column to predict.
• Optionally drop any irrelevant columns.
• Select feature selection method.
• Click Proceed to get model evaluation results!

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💻 Terminal Version: How to Run

You can also run the same logic directly in the terminal:

▶️ Steps:

1. Clone this repo

   git clone https://github.com/RohitXJ/ML-Model-Evaluation-Dashboard-Scripted.git
   cd ML-Model-Evaluation-Dashboard-Scripted

2. Create a virtual environment (recommended)

   python -m venv venv
   source venv/bin/activate   # On Windows: venv\Scripts\activate

3. Install required packages

   pip install -r requirements.txt

4. Run the script

   python main.py

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📦 Requirements

Install with:

pip install -r requirements.txt

Key libraries used:

• pandas
• numpy
• scikit-learn
• matplotlib
• seaborn
• streamlit

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📸 Screenshots

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👥 Author & Contact

Rohit Gomes B.Tech CSE (AI & ML) | Brainware University LinkedIn: @rohit-gomes Email: gomesrohit92@gmail.com GitHub: @RohitXJ

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🙌 Contributions

Pull requests are welcome. For major changes, please open an issue first to discuss your ideas.

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📝 License

MIT License