Performance Analysis of Different Classifiers Used In Detecting Benign And Malignant Cells of Breast Cancer

ABSTRACT: Breast cancer is the most common disease now a days. To get an early detection the target is to find an
efficient way to use scientific investigation, because early detection is the only way to remove cancer cell. To predict the
accuracy of breast cancer detection, researchers have used different classification techniques. In this paper random forest,
Support vector machine, XGBoost, ANN and CNN have been used to analyze and compare the performance. A
comparative study is done on these five classifiers using different accuracy measurements like performance, accuracy
rate. This study shows that CNN gives the high performance among others.

Keywords: ANN, CNN, performance, classification, breast cancer.

Proceedings of International Exchange and Innovation Conference on Engineering &
Sciences (IEICES). 6, pp.243-248, 2020-10-22. Interdisciplinary Graduate School of Engineering
Sciences, Kyushu University.