DESIGN AND COMPARATIVE ANALYSIS OF PERFORMANCE EVALUATION OF ALGORITHMS FOR DETECT BREAST CANCER

Abstract

According to the WHO database, causes of breast cancer are a large number of deaths of women around the world. The prediction of medical disease can be efficiently done by machine learning techniques, especially in the health care sector where these systems are broadly used for detection and evaluation of dataset. This study is trying to obtain the best accurate result with the help of classification techniques. To find out the result we applied Breast Cancer (original) datasets on the proposed classifier which were taken from UCI. Us-ing our proposed machine learning algorithms, we try to find out the best classifier. The main purpose of this analysis is to obtain correctly classified model for evaluating breast cancer da-tasets.  We compare the machine learning algorithms which are respectively Logistic Regres-sion, Random Forest, Sequential Minimal Optimization and Proposed deep learning algo-rithm. All of algorithms applied on classifier tool in sequence manner and obtained the exper-imental results which conclude that Proposed deep learning algorithm lead the maximum ac-curacy (98%) among the all classifier algorithms.