The invention relates to a hierarchical prediction method of the II
type diabetes mellitus incidence probability and belongs to the technical field of
biological information processing. According to the method, firstly, risk grades of II
type diabetes mellitus groups are judged, then, a
package method is adopted for carrying out attribute selection for the groups in different risk grades, and the key incidence risk attribute is selected; next, a naive
bayesian algorithm is utilized for calculating the individual initial incidence probability; and the individual initial incidence probability and a
single step transfer matrix are used to build a
Markov chain, so a II
type diabetes mellitus incidence probability
prediction system is built by aiming at the groups in different risk grades. Compared with the prior art, the hierarchical prediction method has the advantages that the prediction accuracy of the II type
diabetes mellitus incidence probability is further improved, meanwhile, prediction models corresponding to the risk grade can be selected according to different individual input data, the incidence probability in many years is predicated, and the
processing speed is high. The goals of reducing (or delaying) the incidence of the II type
diabetes mellitus can be reached through finding the II type
diabetes mellitus early, taking the II type diabetes mellitus into account early and intervene in the II type diabetes mellitus in advance.