This paper explores the regulation principle of the parameters and some intrinsic localization about Fuzzy Min-Max algorithm. It presents the relationship between the parameters and the training data by using similarity measurement mentioned by Multivariate State Estimation Technique, and implements the nonlinear operation of the measurement by using closeness degree function of fuzzy set theory. It realizes dynamic design of the parameters and promotes the accuracy of classification. By practical application, its validity is proved.