Divide the model construction application into two stages: encoding and decoding stages; Coding stage: perform M division among K categories. Each division divides part of the data into positive categories and part of the data into negative categories. Each division builds a model. The result of the model is for each Each category defines a point; Decoding stage: Use the trained model to predict the test sample, define the sample to be predicted as a point in the space, calculate the distance between the point to be tested and the category, and select the category with the closest distance as the final forecast category.