A new semi-supervised fuzzy clustering method based on latent representation learning and information fusion

Hengdong Zhu, Baoshuo Kan, Yong Li, Enliang Yan, Heng Weng, Fu Lee Wang, Tianyong Hao

Abstract: Highlights•A novel semi-supervised fuzzy clustering method called LIF-SFC is proposed.•The latent representation learning captures low-dimensional manifold structure.•The representation learning and clustering are mutually updated and optimized.•The fusion of pairwise constraint and label information guides clustering jointly.•Comprehensive experiments show that LIF-SFC achieves state-of-the-art performance.