The objective of this project is to create a predictive model that can accurately classify breast cancer cases as benign or malignant based on a set of relevant features.
Dataset overview
- Age: Age of the patient at the time of diagnosis.
- Menopause status: Whether the patient has undergone menopause or not.
- Tumor size: The size of the tumor in millimeters.
- Number of involved lymph nodes: The number of lymph nodes that contain cancer cells.
- Node caps status: Whether the cancer cells have spread to the lymph node capsule or not.
- Degree of malignancy: The degree to which the cancer cells differ from normal cells.
- Breast quadrant location: The quadrant of the breast where the tumor is located.
- Radiation therapy: Whether or not the patient received radiation therapy after surgery.
Used Algorithms
-
| SVM |
-
| Logistics Regression |
-
| Keras Model |
-
| Random Forest |
Best Model : Random Forest with accuracy = 87.5%