Abstract：In consideration of the generalized application of confusion matrix as an important algorithmic measurement tool in machine learning field, a three-way decision measure system of the probabilistic rough set is constructed based on three-way decision confusion matrix. Then, the properties of partial three-way decision measures are discussed. A multi-object optimization function model for three-way decisions thresholds computing is proposed as well. In this model, multi-object optimization functions are considered as weighted sums of three-way decisions measures ,and a new semantic interpretation is acquired for solving the optimal threshold. Finally, the solving process of accepting and rejecting thresholds of the model is demonstrated via an case. By comparing with the classic Pawlak rough set method and confusion matrix model, the confusion matrix model can better balance the accurate rate and the commitment rate for three-way decisions.
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2017, Vol. 30 
