Multi-view clustering considers the diversity of different views and fuses these views to produce a more accurate and robust partition than single-view clustering. In this paper, we proposes a multi-view fuzzy co-clustering algorithm for high-dimensional data classification. We call MvFCoC algorithm. The proposed algorithm is demonstrated through experiments on benchmark data sets. The experimental results show that the clustering quality is better by evaluating using validity indexes in comparison with previous methods.
