Breast Cancer Prediction
This repository contains a breast cancer prediction model built using machine learning techniques. The model is deployed using Flask, providing a user-friendly web interface to predict whether a breast tumor is benign or malignant.
The breast cancer prediction model is developed using a dataset containing various features extracted from breast tumor images. The model leverages state-of-the-art machine learning algorithms to predict the diagnosis. For this project, we utilized the popular scikit-learn library to build and train the model.
The dataset used to train and test the model is obtained from a reliable source (mention the source, like UCI Machine Learning Repository or Kaggle). It consists of labeled samples with features related to breast tumor characteristics.
To run the Flask application and use the breast cancer prediction model, you need the following dependencies:
- Python
- Flask
- scikit-learn
- pandas
- numpy
You can install the required packages using pip. For example:
pip install flask scikit-learn pandas numpy- Clone this repository to your local machine:
git clone https://github.com/your-username/breast-cancer-prediction.git- Change into the project directory:
cd breast-cancer-prediction- Run the Flask application:
python app.py-
Once the Flask app is running, open your web browser and go to
http://localhost:5000to access the breast cancer prediction interface. -
Enter the required tumor features in the provided input fields and click the "Predict" button to get the prediction result.
Contributions to improve the model, web interface, or any other aspect of this project are welcome. If you find any bugs or have suggestions for enhancements, please feel free to create an issue or submit a pull request.
This project is licensed under the MIT License.
Special thanks to IAP and the creators of the dataset used in this project for providing valuable resources.