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https://github.com/harshita2234/breast-cancer-prediction
A machine learning project to predict breast cancer using logistic regression. This project includes data preprocessing, feature scaling, model training, and evaluation, based on a guided project from Coursera.
https://github.com/harshita2234/breast-cancer-prediction
breast-cancer-prediction jupyter-notebook logistic-regression machine-learning matplotlib numpy pandas scikit-learn
Last synced: about 16 hours ago
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A machine learning project to predict breast cancer using logistic regression. This project includes data preprocessing, feature scaling, model training, and evaluation, based on a guided project from Coursera.
- Host: GitHub
- URL: https://github.com/harshita2234/breast-cancer-prediction
- Owner: harshita2234
- License: mit
- Created: 2024-05-31T18:39:51.000Z (8 months ago)
- Default Branch: main
- Last Pushed: 2024-05-31T18:46:23.000Z (8 months ago)
- Last Synced: 2024-12-02T11:12:29.682Z (about 2 months ago)
- Topics: breast-cancer-prediction, jupyter-notebook, logistic-regression, machine-learning, matplotlib, numpy, pandas, scikit-learn
- Language: Jupyter Notebook
- Homepage:
- Size: 43 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Breast Cancer Prediction
This project uses machine learning to predict breast cancer based on features of cell nuclei present in the breast cancer dataset. It is based on a guided project from Coursera.
## Project Description
The goal of this project is to build a logistic regression classifier that can accurately predict whether a tumor is benign or malignant based on certain features. The dataset used is the Breast Cancer Wisconsin (Diagnostic) Dataset.
## Dataset
The dataset contains 569 instances of tumors, with 30 features each. The features are computed from a digitized image of a fine needle aspirate (FNA) of a breast mass. They describe characteristics of the cell nuclei present in the image.
## Project Structure
- `breast_cancer_prediction.ipynb`: Jupyter notebook containing the code for the project.
## Requirements
The project requires the following Python packages:
- pandas
- numpy
- scikit-learn
- matplotlib (optional, for visualizations)
You can install these using pip:
```bash
pip install pandas numpy scikit-learn matplotlib
```
## Usage
1. Clone the repository:
```bash
git clone https://github.com/harshita2234/Breast-Cancer-Prediction.git
```
2. Navigate to the project directory:
```bash
cd Breast-Cancer-Prediction
```
3. Open the Jupyter notebook:
```bash
jupyter notebook breast_cancer_prediction.ipynb
```
4. Run the cells in the notebook to see the analysis and results.
## License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
## Acknowledgments
- Coursera for the guided project
- Wisconsin Diagnostic Breast Cancer (WDBC) dataset