Breast Cancer Detection using Principal Component Analysis and Machine Learning Models

Abstract

Breast cancer is one of the major problems in women. It accounts at least 14% in Indian women. It is a most common form of cancer in women. Breast cancer is spreading in rural as well as urban areas. Approximately, 87,090 deaths and 1,62,468 new cases are reported in the year 2018. Breast cancer detection at an early stage and diagnosis can increase the lives of women. Our work deals with a breast cancer detection system that facilitates user to detect breast cancer using principal component analysis (PCA) and machine learning models (MLMs) based on the features of the data. Five different models are trained and tested to determine which model gave the highest accuracy on the data. The obtained accuracy, precision, sensitivity, and F-Measure are 97.53%, 97.59%, 95.75%, and 96.66%, respectively. The proposed method gave accurate and effective results compared to existing methods. Thus, this provides an effective application of machine learning models in the field of healthcare.