Binary Orthogonal Non-negative Matrix Factorization
Machine Learning
2022-10-20 v1 Optimization and Control
Abstract
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.
Cite
@article{arxiv.2210.10660,
title = {Binary Orthogonal Non-negative Matrix Factorization},
author = {S. Fathi Hafshejani and D. Gaur and S. Hossain and R. Benkoczi},
journal= {arXiv preprint arXiv:2210.10660},
year = {2022}
}