Data Analysis on Biopsies of Breast Cancer Tumors Data Using Data Science

Data Science is a blend of various tools, Algorithms and Machine Learning Principles to extract knowledge from the structured and unstructured data. It is an important scientific field which uses statistics, computing science and intelligence Science to uncover the insights and trends in the data. Data Science is playing a crucial role in medical field. In this study, biopsy of breast cancer patient’s data is considered to uncover the insights of the data that can help to improve the breast cancer diagnosis accuracy. The biopsy data is preprocessed to manage the missing values and the data is visualized through various graphs to demonstrate the data distribution. Supervised learning classifiers such as Support Vector Machine (SVM), K-Nearest Neighbors (KNN) and Feed-forward Neural Network (FNN) are used to classify the data. The performance of each classifier is compared and the best classifier that can classify the biopsy data efficiently is analyzed.