Model parameter adjusting method and device, storage medium and program product

Abstract

Disclosed are a model parameter adjusting method and device, a storage medium and a program product. The method includes: performing classification processing on input data by using a classification model obtained through training based on secure multi-party computing, to obtain classification prediction values of the classification model (S); performing reduction processing on the classification prediction values (S); performing normalization processing on the classification prediction values subjected to the reduction processing, to obtain a normalization result of the classification prediction values (S); and updating a parameter of the classification model according to the normalization result of the classification prediction values (S). Input values for a normalization method are reduced by means of performing the reduction processing on the classification prediction values, such that generation of data overflow can be avoided in a normalization process, thus the training precision of the classification model can be improved.