• Pretty Pramod Kotian
• Snehal Babar
• Aishwarya Ningdali
• Muskan Altaf Shaikh

Breast cancer starts in the breast cell. It is a cancerous tumor where cancer cells grow and destroy nearby tissue. It was estimated in 2019 that 270,000 new breast cancer cases were diagnosed which is an alarming rise of cancer in women every year. With the advances of computer technology, we can save a life from cancer at an earlier stage. Hence, we have built the software with the help of machine learning to analyze breast cells before it gets fatal. This project aims to use machine learning algorithms and techniques to detect breast cancer and also do the prediction with Random Forest, KNN (k-Nearest-Neighbor) and Support Vector Machine algorithm. The Breast Cancer Wisconsin original dataset is used as a training set to compare the performance of the various machine learning techniques in terms of key parameters such as accuracy, and precision. We will perform data visualization in the form of graphs like histograms, boxplots and also study the correlation between each attribute. In the end, we will develop a classification report and confusion matrix to predict whether the dataset is benign or malignant breast cancer for every machine learning algorithm.

Breast Cancer, Machine learning, Prediction, KNN and SVM.

"Breast Cancer Detection using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 12, page no.e407-e413, December-2021, Available :http://www.jetir.org/papers/JETIR2112452.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 12, page no. ppe407-e413, December-2021, Available at : http://www.jetir.org/papers/JETIR2112452.pdf