NONPARAMETRIC DEEP CLUSTERING

Non-parametric deep clustering is a method that leverages deep learning techniques for cluster analysis, with its core being the ability to infer the optimal clustering structure without predefining the number of clusters. This approach aims to uncover latent patterns and structures from complex high-dimensional data, enhancing the accuracy and robustness of clustering. It is widely applied in fields such as image recognition, natural language processing, and bioinformatics, holding significant research and application value.