Breast Cancer Classification Using Machine Learning

Abstract

Manual determination of breast cancer takes a lot of time sometimes weeks or
months and is perilous with a high pace of morbidity, mortality and can involve
human error. an early assurance will help the treatment of this sickness. So,
determination of breast cancer using machine learning model result in quick
identification of tumor. This research paper focuses on early determination of
breast cancer as benign or malignant. with the help breast cancer dataset,
the research paper aims to produce a better decision-making visualization pattern through swarm plots and heat maps. To accomplish this, we utilized Light
GBM Calculation and furthermore contrasted our model’s exhibition and other
surviving ML models specifically Logistic Regression, Gradient Boosting Algorithm, Random Forest Algorithm and XG Boost Algorithm. We were able to
achieve the highest accuracy of 97.07% with the Light GBM Algorithm.