Method and apparatus for training classification model, and method and apparatus for classifying data

Abstract

This application discloses a method and an apparatus for training a classification model. The method includes obtaining a training sample, the training sample including a training parameter and a true classification corresponding to the training parameter and preforming classification training on an initial classification model by using the training parameter, to obtain a predicted classification. The method also includes determining a residual between the true classification and the predicted classification according to a gradient loss function of the initial classification model, the gradient loss function comprising a distance factor representing a distance between a first category and a second category, the first category being a category to which the predicted classification belongs, and the second category being a category to which the true classification belongs. The method further includes modifying the initial classification model according to the residual to obtain a final classification model.