© 2020 JETIR November 2020, Volume 7, Issue 11 www.jetir.org (ISSN-2349-5162) JETIR2011009 Journal of Emerging Technologies and Innovative Research (JETIR) www.jetir.org 51 Abstract: There are many types of cancers that need our attention and a lot of human time spent in researching for their cure by analyzing a lot of symptoms. Many patients with similar health problems receive different kinds of treatment and eventually different extents of cure. Breast Cancer is one of the most exquisite and internecine disease among all of the diseases in medical science. It’s mainly effective for women. It is one of the crucial reasons of death among the females all over the world. Various supervised machine learning techniques such as Logistic Regression,Decision tree Classifier,Random Forest ,K-NN,Support Vector Machine has been used for classification of data .The very famous data set such as Wisconsin breast cancer diagnosis (WBCD) data set has been used for classification of data. The experimental result shows that the Random Forest classifier gives the highest accuracy of 96.50% among the other classifier. The aim is for early detection of cancer because the early detection of cancer can be helpful to remove the cancer completely. Keywords: Machine Learning, Classification, Decision tree Classifier, K-Nearest Neighbor, Logistic Regression, Random Forest,Support Vector Machine,accuracy etc. I. Introduction Machine learning (ML) is a significant method for data analysis that iteratively learns from the available data with the aid of learning algorithms. Machine learning can be defined as a technique for programming computers to optimize a performance criterion using example data or past experience i.e, defining a model up to some parameters, and learning by executing a computer program to optimize the parameters of a model using the training data or past experience. The model has been made predictive to make predictions in the future or descriptive to gather some knowledge/information from data. Machine learning is an artificial intelligence (AI) application that enables systems to learn and improve automatically without being explicitly programmed. Machine learning focuses on developing programs that are able to use the data and to learn from it. Breast Cancer is the prime reason for death of women. It is the second most dangerous cancer after lung cancer. Breast cancer is the most common cancer among women worldwide accounting for 25 percent of all cancer cases. In the year 2018 according to the statistics provided by World Cancer Research Fund it is estimated that over 2 million new cases were recorded out of which 626,679 deaths were approximated. Of all the cancers, breast cancer constitutes of 11.6% in new cancer cases and come up with 24.2% of cancers among women [1]. Most of the experienced researchers come to conclusion that the most experienced physicians/oncologist can diagnose cancer with 79 percent accuracy while 91 percent correct diagnosis has been achieved using machine learning techniques. The procedure for early diagnosis of breast cancer must be accurate and reliable to distinguish between benign breast tumours from malignant ones. II ) Related Work 1) The problem of detection of breast cancer from the set of symptoms attracted many researchers worldwide. Ebrahim et. al [2], have proposed the experiments using Wisconsin Diagnosis Breast Cancer database to classify Breast cancer Prediction using Machine Learning Techniques Ashok Deulkar, Dr.J.A.Laxminarayana Dept.of Computer Science & Engg.,Goa College Of Engineering, Farmagudi-Goa, India, 2 Head of Department, Computer Science & Engg.,Goa College Of Engineering, Farmagudi-Goa, India.