The invention relates to a
nerve network clustering method based on iteration. The method comprises steps that 1, parameters of an over-limit
learning machine model are initiated; 2, samples having the same number as the required clustering number are randomly selected, each sample represents one clustering, an initial
model sample set is formed, and an initial over-limit
learning machine model is acquired through training; 3, clustering grouping for the samples is carried out by utilizing the initial over-limit
learning machine model, and a clustering result is acquired; 4, for each clustering group, multiple samples are selected according to rules as models of the clustering groups; 5, the model samples of each clustering group acquired in the step 4 are utilized to update the over-limit learning
machine model; and 6, the process returns to the step 3 for iteration till the clustering groups are stable or iteration frequency requirements are satisfied, and the clustering groups are acquired and outputted. The method solves a high-dimensional non-linear
data space clustering problem and further solves problems of large memory consumption and long
operation time.