Label-dependent loss function for discrete ordered regression model

A processing apparatus comprising:

• one or more memories storing instructions;
• one or more processors that, upon executing the stored instructions;
• are configured to perform operations including
• obtaining a plurality of images having been evaluated by different sources such that each source has classified each of the plurality of image as being a member of one of a predefined class;
• generating a distribution array identifying a number of times each image of the plurality of images has been classified into each of the predefined classes;
• generating, for each predefined class, a loss function based on the ratio of a number of images in other classes of the predefined classes to a number of images to this predefined classes;
• providing the generated loss function for each predefined class as evaluation parameters to a model;
• using the generated loss function to determine that the model classifies raw image data as being a member of one of the predefined classes according to a predetermined accuracy threshold.