Abstract: The present invention relates to a diabetes early warning system. The system comprises: a memory; and a first processor, which is based on improved k-means clustering, coupled to the memory, and configured to: according to selected first clustering centroids, obtain stable centroids for individual clusters, and put them in a diabetes piecewise function, thereby obtaining a diabetes early warning model, wherein the first clustering centroid is selected by selecting a data set, defining a clustering cluster number k and a neighborhood radius ?, and selecting a sample point on which a sum of distances between a sample point Xi and a sample is the greatest as the first clustering centroid, so as to make the first clustering centroid fall in a central portion of the corresponding cluster.