A Review on Various Matrix Factorizaton Techniques
Keywords:
Matrix Factorization, Non Negative Matrix Factorization, Singular Value DecompositionAbstract
In this work, we give the related work of fundamental matrix decomposition techniques. The primary strategy that we talk about is known as Eigen value decomposition, which breaks down the underlying matrix into an authoritative shape. The second strategy is nonnegative matrix factorization (NMF), which factorizes the underlying grid into two littler matrixes with the imperative that every component of the factorized matrix ought to be nonnegative. The third strategy is singular value decomposition (SVD) that utilizations particular estimations of the underlying network to factorize it. The last technique is CUR decomposition, which faces the issue of high thickness in factorized matrixes (an issue that is confronted when utilizing the SVD strategy). This work concludes with a description of other state-of-the-art matrix decomposition technique.
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