A Comparative Study on Performance of Breast Tissues Classification Using Support Vector Machine and Regression

  • Meenakshi Srivastava

Abstract

The growth of digital devices in various fields like medical, education and science has resulted in generation of massive amount of data. Machine learning algorithms have played a major role in designing computational system which can analyze this massive amount of data in time efficient manner. Classification algorithms are example of supervised learning which identify the category/class to which a new data will fall under. In the present paper Logistic Regression and Support Vector Machine classification algorithms have been analyzed on dataset with electrical impedance measurements in samples of freshly excised tissue from the breast. Performance of both algorithms has been measured and compared on achieved accuracy level and F1 score.

Published
2020-04-18
How to Cite
Meenakshi Srivastava. (2020). A Comparative Study on Performance of Breast Tissues Classification Using Support Vector Machine and Regression. International Journal of Advanced Science and Technology, 29(8s), 258 - 263. Retrieved from http://sersc.org/journals/index.php/IJAST/article/view/10497