Probabilistic spatial clustering based on the Self Discipline Learning (SDL) model of autonomous learning. (arXiv:2201.03449v2 [cs.LG] UPDATED)

Unsupervised clustering algorithm can effectively reduce the dimension of
high-dimensional unlabeled data, thus reducing the time and space complexity of
data processing. However, the traditional clustering algorithm needs to set the
upper bound of the number of categories in advance, and the deep learning
clustering algorithm will fall into the problem of local optimum. In order to
solve these problems, a probabilistic spatial clustering algorithm based on the
Self Discipline Learning(SDL) model is proposed. The algorithm is based on the …

arxiv autonomous clustering learning