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Classifying Breast Cancer Based on Machine Learning

  • Archana BalyanEmail author
  • Yamini Singh
  • Shashank
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1164)

Abstract

Breast cancer is the most prevalent cancer among Indian women and a prime cause of death due to cancer. Hence, an early detection and accurate diagnosis and staging of breast cancer are crucial in managing the disease. In this work, a comparative study of application of machine learning classifiers has been done for the classification of benign from malignant breast cancer. This paper investigates the performance of various supervised classification techniques like logistic regression, support vector machine, k-nearest neighbour and decision tree. These algorithms are coded in R and executed in R studio. For performance analysis, various parameters such as specificity, sensitivity and accuracy have been calculated and compared. The SVM classifier gives the accuracy of 99.82% indicating its suitability over other classification techniques. In this work, we have addressed the issue of distinguishing benign from malignant breast cancer.

Keywords

Breast cancer Classification accuracy SVM Machine learning classifiers Data set 

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Copyright information

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021

Authors and Affiliations

  1. 1.Maharaja Surajmal Institute of TechnologyDelhiIndia

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