Framework for the Classification of Imbalanced Structured Data Using Under-sampling and Convolutional Neural Network

Among machine learning techniques, classification techniques are useful for various business applications, but classification algorithms perform poorly with imbalanced data. In this study, we propose a classification technique with improved binary classification performance on both the minority and majority classes of imbalanced structured data. The proposed framework is composed of three steps. In the first step, a balanced training set is...