关键词: 序贯三支决策, 粒结构, 多类分类, 增量方法

Abstract: In the practical application of the multi-category classification problem, when the cognition of the decision object changes from coarse-grained to fine-grained, by using the granular structure, a sequential three-way decisions model based on multi-category classification is proposed. On this basis, it is time-consuming to computer sequential three-way decisions with the non-incremental method of this model. For the change of conditional attributes in the decision table, the incremental method of the model is given to make the decision. First, the condition attribute of each level is obtained by adding new attributes, and a multilevel granular structure is constructed. Under the multilevel granular structure, the loss function matrix of each level decision table is given. Then thresholds of each decision class are calculated and decisions of each level decision table are made in order. Finally, a sequential three-way decisions algorithm for multi-category classification is given. An example is used to illustrate the calculation process of the   algorithm. In order to dynamically update a sequence of three regions, an incremental algorithm for calculating      sequential three-way decisions is given based on multi-category classifications. The effectiveness of the proposed method is verified by simulation experiments.

Key words: sequential three-way decision, granular structure, multi-category classification, incremental approach