Comparision of Classification Algorithims for Survival of Breast Cancer Patients

Breast cancer has become one of the most common diseases, especially among women, increasing the importance of predicting survival. In this study, the successes of machine learning algorithms on survival prediction were compared using the Surveillance, Epidemiology, and End Results (SEER) breast cancer data set. Used machine learning algorithms are: Naive Bayes, J48, Multiobjective Evolutionary Fuzzy Classifier (MEFC), Support Vector Machines (SVM). The most successful algorithm is J48 algorithm. The most successful algorithm is J48 algorithm according to the tests.