Breast Cancer Prediction Web App

A Streamlit-based web application for predicting breast cancer types based on preprocessed input features. Users select values from predefined options, and the app outputs the predicted cancer type using a trained machine learning model.

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Features

• Interactive UI with st.number_input, st.selectbox, and other input widgets.
• Backend preprocessing already applied; user only selects values.
• Handles prediction with a trained ML model.
• Clean, user-friendly interface.

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Installation

1. Clone the repository:

git clone https://github.com/yourusername/breast-cancer-streamlit.git
cd breast-cancer-streamlit

Create a virtual environment

python -m venv venv
# Linux/Mac
source venv/bin/activate
# Windows
venv\Scripts\activate

Install dependencies:

pip install -r requirements.txt

Project

breast-cancer-streamlit/
│
├── main.py           # Streamlit app
├── model.pkl         # Trained ML model
├── requirements.txt  # Dependencies
├── README.md
└── data/             # Optional folder for input CSV or preprocessed data

Usage

streamlit run main.py

Open the URL provided in the terminal (usually http://localhost:8501) to access the app.

Dependencies

• Python 3.9+
• Streamlit
• scikit-learn
• pandas
• numpy

Install all dependencies via:

pip install -r requirements.txt

Credit

Developed by Muhammad Fiaz