  We propose a method for computing binary orthogonal non-negative matrix
factorization (BONMF) for clustering and classification. The method is tested
on several representative real-world data sets. The numerical results confirm
that the method has improved accuracy compared to the related techniques. The
proposed method is fast for training and classification and space efficient.
