Coclustering of Multidimensional Big Data: A Useful Tool for Genomic, Financial, and Other Data Analysis
Hong Yan · IEEE Systems Man and Cybernetics Magazine · 2017
In summary, coclustering provides classifications simultaneously in all directions of a multidimensional data array. It may be used to detect coherent patterns that are embedded in a large matrix or tensor and contain a subset of elements in each direction. It can be performed effectively in singular -vector spaces based on hyperplane detection. We expect that coclustering will gain more and more applications in machine learning, image processing, bioinformatics, and big data analytics.