Breast cancer is a type of cancer that begins in the cells of the breast tissue. It is one of the most common cancers affecting women worldwide, although it can also occur in men. Breast cancer forms when normal cells in the breast undergo genetic mutations that cause them to grow and divide uncontrollably, forming a mass or tumor. If left untreated, breast cancer cells can invade nearby tissues and spread to other parts of the body, a process known as metastasis. Breast cancer detection using machine learning involves leveraging algorithms and computational techniques to analyze medical imaging data, such as mammograms, to assist in the early detection and diagnosis of breast cancer.
The original data is taken from Breast Cancer Wisconsin (Diagnostic) from UCI Machine Learning Repository
- Data Preparation
- Data Exploration
- Handling Categorical Data such as Label Encoding
- Feature Scaling
- Model Selection
- Model Testing
- Prediction Analysis
We obtain promising high accuracy results on various multiple classifiers . After applying the different classification models, we employ the best accurate model having 0.9635 accuracy with KNN and SVM models.