AutoEIS: Automatic feature embedding, interaction and selection on default prediction

Kai Xiao, Xiaohan Jiang, Peng Hou, Hongbin Zhu

Abstract: Highlights•We propose an automatic end-to-end DL framework coined AutoEIS for default prediction.•We propose a MfMoE structure for numerical feature embedding.•We integrate multiple strategies to effectively generate significant interactions.