Binary Classification Web App

This is a web app built to dynamically select a classifier from the given options along with their respective hyper-parameters and view the results in three formats.

Classifiers Used

• Support Vector Classifier (SVC)
• Logistic Regression
• Random Forest Classifier

Metrics Used

• Confusion Matrix
• ROC Curve
• Precision-Recall Curve

Built With

• Streamlit - The web framework used
• scikit-learn - Machine learning library
• pandas - Data manipulation and analysis
• numpy - Numerical computing

Deployment

(https://arnavballincode-binary-classifier-app-kt94ps.streamlit.app/)

Getting Started

Prerequisites

Make sure you have the following installed:

• Python 3.6 or higher
• pip (Python package installer)

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/binary-classification-web-app.git
   cd binary-classification-web-app

2. Create a virtual environment:

   python -m venv myenv

3. Activate the virtual environment:

   • On Windows:

     myenv\Scripts\activate

   • On macOS and Linux:

     source myenv/bin/activate

4. Install the required packages:

   pip install -r requirements.txt

5. Run the app:

   streamlit run app.py