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 pat- tern 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 Algo- rithm, Random Forest Algorithm and XG Boost Algorithm. We were able to achieve the highest accuracy of 97.07% with the Light GBM Algorithm.
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