Joint Learning of Fuzzy <italic>k</italic>-Means and Nonnegative Spectral Clustering With Side Information

As one of the most widely used clustering techniques, the fuzzy k-means (FKM) assigns every data point to each cluster with a certain degree of membership. However, conventional FKM approach relies on the square data fitting term, which is sensitive to the outliers with ignoring the prior information. In this paper, we develop a novel and robust fuzzy k-means clustering algorithm, namely, joint learning of fuzzy k-means and nonnegative spectral...