Stochastic Markov $k$-Tree Network Sparsification Learning for Image Classification

Classification in computer science is for the purpose of designing and implementing an algorithmic classifier to identify the target category given by an observed data, which has played a key role within the recent decades. The author, in this paper, proposed a novel image classification learning method associated with machine learning by introducing network sparsification modelling algorithm based on stochastic Markov k-tree graph learning. The proposed Markov k-tree network sparsification learning demonstrated its overall state-of-art performance, as our testing and analysis proved, on multiple datasets which are generally well-used for the image classification application.