Rough set is a data mining theory for uncertainty data, and neighborhood rough sets are common models for dealing with mixed data. In order to improve the anti noise ability of mixed data, a variable precision rough set model of the mixed information system is proposed. Due to the dynamics of the information system in the real environment, this paper further proposes a dynamic variable precision rough set model when the object is increased and reduced. Firstly, the changed relation of conditional probability with the increasing and decreasing object in the mixed information system is studied. Then, on the basis of this changed relation, an incremental updating mechanism of the upper and lower approximation of the variable precision rough set of the mixed information system is proposed. Finally, according to this updating mechanism, the corresponding incremental approximation updating algorithm is proposed. Experimental results show that the proposed incremental updating algorithm has higher computational efficiency than the non-incremental algorithm, thus the effectiveness of the proposed model is validated, meanwhile, the proposed model is more suitable for complex data environments.