The problem of incremental attribute reduction for incomplete hybrid decision systems has been a hot topic of research in re-cent years.A definition of knowledge granularity for an incomplete hybrid decision system is given for the case where attribute values and attributes change at the same time.Based on the refinement of the incremental mechanism based on the knowledge granularity,an improved incremental attribute reduction algorithm with attribute value change and increasing attributes is proposed.And the simulation experiments are verified with eight datasets on UCI.The results show that the proposed incremental attribute reduction algorithm has higher reduction efficiency and better classification performance compared with the non-incremental attribute reduction algorithm and the same type of attribute reduction algorithm.
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