Breast cancer prediction using machine learning techniques

Abstract

The most commonly identified cancer among women is breast cancer and has been identified as the major reason for increasing mortality rate in women. Since there are only fewer resources for diagnosis of cancer diseases there are more need for development of such systems. Data mining has the privilege of playing a vital role in development of such systems. In our paper, we have used machine learning methods to construct and analyse the performance of some selected algorithms for breast cancer diagnosis. In our study, K-Nearest Neighbour (KNN) algorithm was used for the diagnosis of Wisconsin Dataset. The precision, recall, accuracy, sensitivity, specificity was found. The precision and recall values were considerably increased by the application of the steps such as 1. Feature scaling 2. Dimensionality reduction 3. Cross Validation 4. Hyperparameter Optimization. We have found an average accuracy of 94.9%.