Binary collaborative data balance optimization method and system and storage medium

The invention relates to the technical field of model training, and discloses a binary collaborative data balance optimization method and system and a storage medium, and the method comprises the steps: constructing a binary data set on the basis of an original sample data set, the binary data set comprising a minority class set and a majority class set; the main classifier and the auxiliary classifier are trained cooperatively, the main classifier is trained by adopting original sample data, and the auxiliary classifier is trained by adopting a binary data set; correcting the probability vector of each category output by the main classifier according to the output of the auxiliary classifier; calculating the gradient of the loss function to the model parameters according to the total loss, and updating the model parameters by adopting gradient descent optimization; according to the method, the performance of the multi-classification task of the whole model can be improved, especially when the data of the mul