Breast Cancer Prediction System Project in Python Django with Machine Learning
The Breast Cancer Prediction System is one of the most popular and in-demand machine learning projects for students. It is designed using Python Django framework along with powerful machine learning algorithms and libraries. This project is highly suitable for final year computer science projects, mini projects with source code, and for students looking to implement a medical diagnosis prediction system using datasets.
This web-based application helps predict whether a patient is likely to have Benign (non-cancerous) or Malignant (cancerous) tumors by analyzing medical parameters. The system uses the Breast Cancer Dataset and applies RandomForestClassifier with StandardScaler for feature scaling and classification_report for model evaluation. The application ensures accurate results and maintains a prediction history for user reference.
Features of Breast Cancer Prediction System
- Home Page : Static informative landing page.
- About Page : Static page with project details.
- Dashboard : Displays all menu items and modules.
- Breast Cancer Prediction : Takes user input and predicts whether the tumor is cancerous or not.
- Dataset Information : Provides dataset description and statistical analysis.
- Prediction History : Shows past records of user predictions with results.
- Login Module : User authentication for accessing prediction features.
- Change Password : Allows users to reset or update account password.
- Logout : Securely logs out users from the system.
Libraries and Algorithms Used
The project uses the following Python libraries for machine learning:
- Django==5.2.6 (Web Framework)
- joblib==1.5.2 (Model persistence)
- mysqlclient==2.2.7 (Database integration)
- numpy==2.3.3 and pandas==2.3.2 (Data handling)
- scikit-learn==1.7.2 and scipy==1.16.2 (Machine Learning)
- StandardScaler (Feature scaling)
- RandomForestClassifier (Classification algorithm)
- classification_report (Performance evaluation)
This Python Django project with source code and dataset is perfect for students who want to learn how to integrate machine learning algorithms in web applications. It is one of the best machine learning final year projects that combines data science, artificial intelligence, and web development.
