Analysis and Prediction of Breast Cancer using Machine Learning Techniques
Shakkeera L1, Rahul Raj Pandey2, Rahul Bhardwaj3, Sidhya Virya Singh4, Siddhartha S. Mukherjee5

1Shakkeera L*, School of Computing Science and Engineering, VIT Bhopal University, Madhya Pradesh, India.
2Rahul Raj Pandey, School of Computing Science and Engineering, VIT Bhopal University, Madhya Pradesh, India.
3Rahul Bhardwaj, School of Computing Science and Engineering, VIT Bhopal University, Madhya Pradesh, India.
4Sidhya Virya Singh, School of Computing Science and Engineering, VIT Bhopal University, Madhya Pradesh, India.
5Siddhartha S. Mukherjee, School of Computing Science and Engineering, VIT Bhopal University, Madhya Pradesh, India

Manuscript received on November 22, 2020. | Revised Manuscript received on November 25, 2020. | Manuscript published on December 30, 2020. | PP: 16-30 | Volume-10 Issue-2, December 2020. | Retrieval Number: 100.1/ijeat.B19681210220 | DOI: 10.35940/ijeat.B1968.1210220
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Rapid multiplication of cells in the human body leads to cancer. It is the foremost cause of death due to cancer in females, after lung cancer. As the breast cancer is one of the recurrent kinds of cancer, diagnosis of breast cancer recurring is extremelyessential to increase the survival rate of patient suffering from it. Although cancer is avertible and also treatable in primary/early stages yet a vast number of patients are diagnosed with cancer when it is very late. Almost 8% of females are detected with breast cancer. Its characteristics are mutation of genes, constant pain, changes in the size and redness of skin texture of breasts. With the development of technology and machine learning techniques, cancer diagnosis and detection accuracy has greatly improved. This paper presents an outline of evolved machine learning techniques in this medical field by applying machine learning algorithms on breast cancer dataset like Logistic regression, Random Forest, Decision Trees (DT) etc. 
Keywords: Classifier, Classification accuracy, Machine Learning, Prediction.