Support Vector Machine Classifier for Prediction of Breast Malignancy using Wisconsin Breast Cancer Dataset

Cancer is the world's second largest cause of death. In 2018, 9.6 million people died from cancer. any medical sickness, breast cancer one most delicate and endemic diseases. This primary causes female death in world. Breast kills out every eleven women around "Early detection equals improved odds survival," says a well-known adage. As result, early essential for successfully preventing lowering morality. type that affects significant issues humanity has faced recent decades been diagnosis prediction. accurate can save millions lives. Effective technologies diagnosing malignant breasts aid healthcare providers treating patients fast manner. Experiments were carried this study to categorize as benign or using Wisconsin Diagnosis (WDBC) database. Support Vector Machine supervised learning technique (SVM). The SVM classifier's classification performance evaluated. demonstrate model fantastic performance, with accuracy 96.09 percent on testing subset.