A sparse implementation of a binary matrix optimized for row operations. All elements in a binary matrix are element of the binary field GF2. That is, they are either 0 or 1 and addition is modulo 2.

A confusion matrix has four cells that represent the four possible outcomes of a binary classification model: true positives (TP), true negatives (TN), false positives (FP), and false negatives (FN).

Abstract: An interesting problem in nonnegative matrix factorization (NMF) is to factorize the matrix X which is of some specific class, for example, binary matrix. In this paper, we extend the ...

An interesting problem in nonnegative matrix factorization (NMF) is to factorize the matrix X which is of some specific class, for example, binary matrix. In this paper, we extend the standard NMF to ...