Denoising Auto-Encoder-Enhanced Deep Non-Negative Matrix Factorization Clustering Model

Non-negative matrix factorization directly decomposes data features into a base matrix and community matrix, which are easily affected by noise. Multi-view datasets have multiple feature matrices, each with a different angle. The data features need to be re-synthesized rather than simply concatenated or added. Based on the advantages and disadvantages of multi-view clustering and non-negative matrix factorization, we attempt to transplant the method of analyzing abstract connected graphs, analog