RFM analysis for customer segmentation using feature generation and accelerated deep learning for prediction

In this project, we propose a feature generation method for customer segmentation using an online retail store dataset. Also, we perform a comparative cluster analysis between the proposed method and the traditional method with K-means. We show that among the top-7 classifiers reported in previous studies, Multi-layer Perceptron (MLP) is the best. Then, we use the Genetic Algorithm (GA) to improve the speed and accuracy of MLP during the prediction phase.