EFFECTIVE DIAGNOSIS OF BREAST CANCER USING KNN ALGORITHM.

Cancer is one of the deadliest diseases in human beings. Breast cancer is considered to be the second most exposed cancer in the world and is now the most common disease in women. The women of ages 45-59 has the highest number of chances to be affected by breast cancer. Early prediction and diagnosis of breast cancer can prevent its spread and may help with effective treatment or medication. Predicting breast cancer is a very arduous task as the data can be highly Non-linear and may require high level computation modeling. However, many machine learning algorithms like KNN, K-Means, Decision Trees, Neural Networks etc., have proved to be effective in predicting breast cancer. This study shows the use of k-Nearest Neighbors (kNN) algorithm to predict whether a person is having breast cancer or not, using a machine learning model trained with different features. Thus, we inferred that we could predict the Breast Cancer with reasonable accuracy. From the results, it can be concluded that breast cancer cells can be accurately detected using machine learning techniques such as KNN. [ABSTRACT FROM AUTHOR]