• Vanlalhmangaihsanga
• P.C.Vanlalbeiseia
• Laledenthara

In the contemporary world Breast Cancer has become the second leading cause of death among women. Early detection, assessment and followed by appropriate treatment of the cancer can reduce the deadly risk. Technology such as data mining and machine learning can substantially improve the diagnosis accuracy and reduce errors that can be made by medical professionals. This paper emphasizes on the algorithm on which machine can learn to accurately detect breast cancer. Machine Learning algorithm that are composed in this paper are Support Vector Machine, Logistic Regression, K-Nearest Neighbour Classifier, Naïve Bayes, Decision Tree and Random Forest. The Algorithm will be tested accordingly with the World Breast Cancer (WBC) datasets. Benchmarking the aforementioned algorithm and picking the most efficient amongst the algorithm is the aim of this paper.

Breast Cancer, Support Vector Machine, K-Nearest Neighbour Classifier, Logistic Regression, Decision Tree, Random Forest

"Breast Cancer Detection using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 6, page no.b758-b764, June-2021, Available :http://www.jetir.org/papers/JETIR2106248.pdf

"Breast Cancer Detection using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 6, page no. ppb758-b764, June-2021, Available at : http://www.jetir.org/papers/JETIR2106248.pdf