METHOD AND APPARATUS FOR PARAMETER ACQUISITION FOR RECOGNITION MODEL, ELECTRONIC DEVICE, AND STORAGE MEDIUM

A method for parameter acquisition for a recognition model, relating to data processing technology, and comprising: acquiring a training dataset containing a noise tag, and performing data standardization processing on the training dataset to obtain a standard dataset (S1); on the basis of a multi-layer deep neural network, constructing a recognition model, and using the standard dataset to train the recognition model to obtain a standard recognition model containing initialized parameters (S2); constructing a noise probability transition matrix for the standard dataset (S3); on the basis of the noise probability transition matrix, constructing a loss function (S4); and using the loss function to calculate updated parameters for the standard recognition model, thereby obtaining more accurate model parameters (S5). The described method further relates to blockchain technology, and the training dataset can be stored in nodes of a blockchain. Further disclosed are an apparatus for parameter acquisition for a rec