Breast cancer is one of the most common reasons for cancer death. Early detection and diagnosis are very important for the survival of the patient. There are various Machine Learning techniques available for the purpose of diagnosis of Breast Cancer. In this study, we have compared the classification results of Neural Network and Deep Neural Network Technique for classifying Breast Cancer dataset into benign and malignant. In the present study we analyzed the classification results of Neural Network and Deep Neural Network techniques with and without dimensionality reduction techniques (Principal Component Analysis and Linear Discriminant Analysis). We took Wisconsin Diagnostic Breast Cancer dataset available from UCI repository containing 32 attributes. The performance of each technique is evaluated using various performance measures. The classification result shows that Neural Network technique and Deep Learning technique both gives better result in terms of different parameters.
