An interactive Streamlit web application for validating multiple classification models on a single dataset.
Built with: Python, Streamlit, scikit-learn, pandas
Functionality:
Allows users to select different classification algorithms (e.g., Logistic Regression, SVM, Random Forest, etc.).
Users can tune hyperparameters directly from the UI.
Choose which classification metrics to apply (Accuracy, Precision, Recall, F1-score, etc.).
All evaluations are performed on a predefined dataset.
Coming Soon: Upload-your-own-dataset feature for more flexibility and real-world use.
This app is designed to make it easier to compare model performance interactively, all in one place.
python -m streamlit run app.py