The Breast cancer is the most life menacing disease among women. Early prophecy assurances the endurance of patients. In this work, first Deep neural network classifiers with different hidden layers with different nodes are used to explore the anthropometric information and blood investigation strictures and to predict the disease. Then machine learning algorithms such as SVM and Decision tree are also trained with the same data. Finally the performance of each classifier was deliberated. The pre-processed data of admitted patients with the breast cancer perception are used to train and test the classifiers. This article shack glow on the concert estimation based on right and erroneous data classification
Margin Matters: Towards More Discriminative Deep Neural Network Embeddings for Speaker Recognition
